Probability Abstracts 86

This document contains abstracts 3205-3373. They have been mailed on May 2, 2005.

3205. Random graphs with arbitrary i.i.d. degrees

Author(s): Remco van der Hofstad and Gerard Hooghiemstra and Dmitri Znamenski

Abstract: In this paper we study distances and connectivity properties of random graphs with an arbitrary i.i.d. degree sequence. When the tail of the degree distribution is regularly varying with exponent $1-\tau$ there are three distinct cases: (i) $\tau>3$, where the degrees have finite variance, (ii) $\tau\in (2,3)$, where the degrees have infinite variance, but finite mean, and (iii) $\tau\in (1,2)$, where the degrees have infinite mean. These random graphs can serve as models for complex networks where degree power laws are observed. The distances between pairs of nodes in the three cases mentioned above have been studied in three previous publications, and we survey the results obtained there. Apart from the critical cases $\tau=1$, $\tau=2$ and $\tau=3$, this completes the scaling picture. We explain the results heuristically and describe related work and open problems. We also compare the behavior in this model to Internet data, where a degree power law with exponent $\tau\approx 2.2$ is observed. Furthermore, in this paper we derive results concerning the connected components and the diameter. We give a criterion when there exists a unique largest connected component of size proportional to the size of the graph, and study sizes of the other connected components. Also, we show that for $\tau\in (2,3)$, which is most often observed in real networks, the diameter in this model grows much faster than the typical distance between two arbitrary nodes.

http://arXiv.org/abs/math/0502580
http://front.math.ucdavis.edu/math.PR/0502580 (alternate)

3206. The Single Server Queue and the Storage Model: Large Deviations and Fixed Points

Author(s): Moez Draief

Abstract: We consider the coupling of a single server queue and a storage model defined as a Queue/Store model in Draief et al. 2004. We establish that if the input variables both arrivals to the queue and to the store satisfy large deviations principles and are linked through an {\em exponential tilting} than the output variables (departures from each system) satisfy large deviations principles with the same rate function. This generalizes to the context of large deviations the extension of Burke's Theorem derived in Draief et al. 2004.

http://arXiv.org/abs/math/0503016
http://front.math.ucdavis.edu/math.PR/0503016 (alternate)

3207. Subexponential asymptotics of hybrid fluid and ruin models

Author(s): Bert Zwart and Sem Borst and Krzystof Debicki

Abstract: We investigate the tail asymptotics of the supremum of X(t)+Y(t)-ct, where X={X(t),t\geq 0} and Y={Y(t),t\geq 0} are two independent stochastic processes. We assume that the process Y has subexponential characteristics and that the process X is more regular in a certain sense than Y. A key issue examined in earlier studies is under what conditions the process X contributes to large values of the supremum only through its average behavior. The present paper studies various scenarios where the latter is not the case, and the process X shows some form of ``atypical'' behavior as well. In particular, we consider a fluid model fed by a Gaussian process X and an (integrated) On-Off process Y. We show that, depending on the model parameters, the Gaussian process may contribute to the tail asymptotics by its moderate deviations, large deviations, or oscillatory behavior.

http://arXiv.org/abs/math/0503482
http://front.math.ucdavis.edu/math.PR/0503482 (alternate)

3208. Deviation inequalities via coupling for stochastic processes and random fields

Author(s): J.-R. Chazottes and P. Collet and C. Kuelske and F. Redig

Abstract: We present a new and simple approach to deviation inequalities for non-product measures, i.e., for dependent random variables. Our method is based on coupling. We illustrate our abstract results with chains with complete connections and Gibbsian random fields, both at high and low temperature.

http://arXiv.org/abs/math/0503483
http://front.math.ucdavis.edu/math.PR/0503483 (alternate)

3209. An approximate sampling formula under genetic hitchhiking

Author(s): A. M. Etheridge and P. Pfaffelhuber and A. Wakolbinger

Abstract: For a genetic locus carrying a strongly beneficial allele which has just fixed in a large population we study the ancestry at a linked neutral locus. During this ''selective sweep'' the linkage between the two loci is broken up by recombination, and the ancestry at the neutral locus is modelled by a structured coalescent in a random background. For large selection coefficients $\alpha$ and under an appropriate scaling of the recombination rate, we derive a sampling formula with an order of accuracy of $O((\log\alpha)^{-2})$ in probability. In particular we see that, with this order of accuracy, in a sample of fixed size there are at most two non-singleton families of individuals which are identi cal by descent at the neutral locus from the beginning of the sweep. This refines a formula going back to the work of Maynard Smith and Haigh, and co mplements recent work of Schweinsberg and Durrett on selective sweeps in the Moran model.

http://arXiv.org/abs/math/0503485
http://front.math.ucdavis.edu/math.PR/0503485 (alternate)

3210. Large deviations of a modified Jackson network: stability and rough asymptotics

Author(s): Robert D. Foley and David R. McDonald

Abstract: Consider a modified, stable, two node Jackson network where server 2 helps server 1 when server 2 is idle. The probability of a large deviation of the number of customers at node one can be calculated using the flat boundary theory of Schwartz and Weiss [Large Deviations Performance Analysis (1994), Chapman and Hall, New York]. Surprisingly, however, these calculations show that the proportion of time spent on the boundary, where server 2 is idle, may be zero. This is in sharp contrast to the unmodified Jackson network which spends a nonzero proportion of time on this boundary.

http://arXiv.org/abs/math/0503487
http://front.math.ucdavis.edu/math.PR/0503487 (alternate)

3211. Bridges and networks: Exact asymptotics

Author(s): Robert D. Foley and David R. McDonald

Abstract: We extend the Markov additive methodology developed in [Ann. Appl. Probab. 9 (1999) 110-145, Ann. Appl. Probab. 11 (2001) 596-607] to obtain the sharp asymptotics of the steady state probability of a queueing network when one of the nodes gets large. We focus on a new phenomenon we call a bridge. The bridge cases occur when the Markovian part of the twisted Markov additive process is one null recurrent or one transient, while the jitter cases treated in [Ann. Appl. Probab. 9 (1999) 110-145, Ann. Appl. Probab. 11 (2001) 596-607] occur when the Markovian part is (one) positive recurrent. The asymptotics of the steady state is an exponential times a polynomial term in the bridge case, but is purely exponential in the jitter case. We apply this theory to a modified, stable, two node Jackson network where server two helps server one when server two is idle. We derive the sharp asymptotics of the steady state distribution of the number of customers queued at each node as the number of customers queued at the server one grows large. In so doing we get an intuitive understanding of the companion paper [Ann. Appl. Probab. 15 (2005) 519-541] which gives a large deviation analysis of this problem using the flat boundary theory in the book by Shwartz and Weiss. Unlike the (unscaled) large deviation path of a Jackson network which jitters along the boundary, the unscaled large deviation path of the modified network tries to avoid the boundary where server two helps server one (and forms a bridge).

http://arXiv.org/abs/math/0503488
http://front.math.ucdavis.edu/math.PR/0503488 (alternate)

3212. Upper bounds for spatial point process approximations

Author(s): Dominic Schuhmacher

Abstract: We consider the behavior of spatial point processes when subjected to a class of linear transformations indexed by a variable T. It was shown in Ellis [Adv. in Appl. Probab. 18 (1986) 646-659] that, under mild assumptions, the transformed processes behave approximately like Poisson processes for large T. In this article, under very similar assumptions, explicit upper bounds are given for the d_2-distance between the corresponding point process distributions. A number of related results, and applications to kernel density estimation and long range dependence testing are also presented. The main results are proved by applying a generalized Stein-Chen method to discretized versions of the point processes.

http://arXiv.org/abs/math/0503491
http://front.math.ucdavis.edu/math.PR/0503491 (alternate)

3213. Noise stability of functions with low influences: invariance and optimality

Author(s): Elchanan Mossel and Ryan O'Donnell and Krzysztof Oleszkiewicz

Abstract: In this paper we study functions with low influences on product probability spaces. The analysis of boolean functions with low influences has become a central problem in discrete Fourier analysis. It is motivated by fundamental questions arising from the construction of probabilistically checkable proofs in theoretical computer science and from problems in the theory of social choice in economics. We prove an invariance principle for multilinear polynomials with low influences and bounded degree; it shows that under mild conditions the distribution of such polynomials is essentially invariant for all product spaces. Ours is one of the very few known non-linear invariance principles. It has the advantage that its proof is simple and that the error bounds are explicit. We also show that the assumption of bounded degree can be eliminated if the polynomials are slightly ``smoothed''; this extension is essential for our applications to ``noise stability''-type problems. In particular, as applications of the invariance principle we prove two conjectures: the ``Majority Is Stablest'' conjecture from theoretical computer science, which was the original motivation for this work, and the ``It Ain't Over Till It's Over'' conjecture from social choice theory.

http://arXiv.org/abs/math/0503503
http://front.math.ucdavis.edu/math.PR/0503503 (alternate)

3214. Logarithmic Sobolev inequality for log-concave measure from Prekopa-Leindler inequality

Author(s): Ivan Gentil

Abstract: We develop in this paper an amelioration of the method given by S. Bobkov and M. Ledoux in GAFA (2000). We prove by Prekopa-Leindler Theorem an optimal modified logarithmic Sobolev inequality adapted for all log-concave measure on $\dR^n$. This inequality implies results proved by Bobkov and Ledoux, the Euclidean Logarithmic Sobolev inequality generalized in the last years and it also implies some convex logarithmic Sobolev inequalities for large entropy.

http://arXiv.org/abs/math/0503476
http://front.math.ucdavis.edu/math.FA/0503476 (alternate)

3215. Equilibrium Glauber and Kawasaki dynamics of continuous particle systems

Author(s): Yu. G. Kondratiev and E. Lytvynov and M. R\"ockner

Abstract: We construct two types of equilibrium dynamics of infinite particle systems in a Riemannian manifold $X$. These dynamics are analogs of the Glauber, respectively Kawasaki dynamics of lattice spin systems. The Glauber dynamics now is a process where interacting particles randomly appear and disappear, i.e., it is a birth-and-death process in $X$, while in the Kawasaki dynamics interacting particles randomly jump over $X$. We establish conditions on a priori explicitly given symmetrizing measures and generators of both dynamics under which corresponding conservative Markov processes exist.

http://arXiv.org/abs/math/0503042
http://front.math.ucdavis.edu/math.PR/0503042 (alternate)

3216. The stepping stone model. II: Genealogies and the infinite sites model

Author(s): Iljana Zahle and J. Theodore Cox and Richard Durrett

Abstract: This paper extends earlier work by Cox and Durrett, who studied the coalescence times for two lineages in the stepping stone model on the two-dimensional torus. We show that the genealogy of a sample of size n is given by a time change of Kingman's coalescent. With DNA sequence data in mind, we investigate mutation patterns under the infinite sites model, which assumes that each mutation occurs at a new site. Our results suggest that the spatial structure of the human population contributes to the haplotype structure and a slower than expected decay of genetic correlation with distance revealed by recent studies of the human genome.

http://arXiv.org/abs/math/0503512
http://front.math.ucdavis.edu/math.PR/0503512 (alternate)

3217. Renewal theory and computable convergence rates for geometrically ergodic Markov chains

Author(s): Peter H. Baxendale

Abstract: We give computable bounds on the rate of convergence of the transition probabilities to the stationary distribution for a certain class of geometrically ergodic Markov chains. Our results are different from earlier estimates of Meyn and Tweedie, and from estimates using coupling, although we start from essentially the same assumptions of a drift condition toward a ``small set.'' The estimates show a noticeable improvement on existing results if the Markov chain is reversible with respect to its stationary distribution, and especially so if the chain is also positive. The method of proof uses the first-entrance-last-exit decomposition, together with new quantitative versions of a result of Kendall from discrete renewal theory.

http://arXiv.org/abs/math/0503515
http://front.math.ucdavis.edu/math.PR/0503515 (alternate)

3218. Utility Maximization with a Stochastic Clock and an Unbounded Random Endowment

Author(s): Gordan Zitkovic

Abstract: We introduce a linear space of finitely additive measures to treat the problem of optimal expected utility from consumption under a stochastic clock and an unbounded random endowment process. In this way we establish existence and uniqueness for a large class of utility-maximization problems including the classical ones of terminal wealth or consumption, as well as the problems that depend on a random time horizon or multiple consumption instances. As an example we explicitly treat the problem of maximizing the logarithmic utility of a consumption stream, where the local time of an Ornstein-Uhlenbeck process acts as a stochastic clock.

http://arXiv.org/abs/math/0503516
http://front.math.ucdavis.edu/math.PR/0503516 (alternate)

3219. Reconstructing a two-color scenery by observing it along a simple random walk path

Author(s): Heinrich Matzinger

Abstract: Let {\xi (n)}_{n\in Z} be a two-color random scenery, that is, a random coloring of Z in two colors, such that the \xi (i)'s are i.i.d. Bernoulli variables with parameter \tfrac12. Let {S(n)}_{n\in N} be a symmetric random walk starting at 0. Our main result shows that a.s., \xi \circ S (the composition of \xi and S) determines \xi up to translation and reflection. In other words, by observing the scenery \xi along the random walk path S, we can a.s. reconstruct \xi up to translation and reflection. This result gives a positive answer to the question of H. Kesten of whether one can a.s. detect a single defect in almost every two-color random scenery by observing it only along a random walk path.

http://arXiv.org/abs/math/0503517
http://front.math.ucdavis.edu/math.PR/0503517 (alternate)

3220. A diffusion model of scheduling control in queueing systems with many servers

Author(s): Rami Atar

Abstract: This paper studies a diffusion model that arises as the limit of a queueing system scheduling problem in the asymptotic heavy traffic regime of Halfin and Whitt. The queueing system consists of several customer classes and many servers working in parallel, grouped in several stations. Servers in different stations offer service to customers of each class at possibly different rates. The control corresponds to selecting what customer class each server serves at each time. The diffusion control problem does not seem to have explicit solutions and therefore a characterization of optimal solutions via the Hamilton-Jacobi-Bellman equation is addressed. Our main result is the existence and uniqueness of solutions of the equation. Since the model is set on an unbounded domain and the cost per unit time is unbounded, the analysis requires estimates on the state process that are subexponential in the time variable. In establishing these estimates, a key role is played by an integral formula that relates queue length and idle time processes, which may be of independent interest.

http://arXiv.org/abs/math/0503518
http://front.math.ucdavis.edu/math.PR/0503518 (alternate)

3221. Exact and approximate results for deposition and annihilation processes on graphs

Author(s): Mathew D. Penrose and Aidan Sudbury

Abstract: We consider random sequential adsorption processes where the initially empty sites of a graph are irreversibly occupied, in random order, either by monomers which block neighboring sites, or by dimers. We also consider a process where initially occupied sites annihilate their neighbors at random times. We verify that these processes are well defined on infinite graphs, and derive forward equations governing joint vacancy/occupation probabilities. Using these, we derive exact formulae for occupation probabilities and pair correlations in Bethe lattices. For the blocking and annihilation processes we also prove positive correlations between sites an even distance apart, and for blocking we derive rigorous lower bounds for the site occupation probability in lattices, including a lower bound of 1/3 for Z^2. We also give normal approximation results for the number of occupied sites in a large finite graph.

http://arXiv.org/abs/math/0503519
http://front.math.ucdavis.edu/math.PR/0503519 (alternate)

3222. Near-integrated GARCH sequences

Author(s): Istvan Berkes and Lajos Horvath and Piotr Kokoszka

Abstract: Motivated by regularities observed in time series of returns on speculative assets, we develop an asymptotic theory of GARCH(1,1) processes {y_k} defined by the equations y_k=\sigma_k\epsilon_k, \sigma_k^2=\omega +\alpha y_{k-1}^2+\beta \sigma_{k-1}^2 for which the sum \alpha +\beta approaches unity as the number of available observations tends to infinity. We call such sequences near-integrated. We show that the asymptotic behavior of near-integrated GARCH(1,1) processes critically depends on the sign of \gamma :=\alpha +\beta -1. We find assumptions under which the solutions exhibit increasing oscillations and show that these oscillations grow approximately like a power function if \gamma \leq 0 and exponentially if \gamma >0. We establish an additive representation for the near-integrated GARCH(1,1) processes which is more convenient to use than the traditional multiplicative Volterra series expansion.

http://arXiv.org/abs/math/0503520
http://front.math.ucdavis.edu/math.PR/0503520 (alternate)

3223. Asymptotics in randomized urn models

Author(s): Zhi-Dong Bai and Feifang Hu

Abstract: This paper studies a very general urn model stimulated by designs in clinical trials, where the number of balls of different types added to the urn at trial n depends on a random outcome directed by the composition at trials 1,2,...,n-1. Patient treatments are allocated according to types of balls. We establish the strong consistency and asymptotic normality for both the urn composition and the patient allocation under general assumptions on random generating matrices which determine how balls are added to the urn. Also we obtain explicit forms of the asymptotic variance-covariance matrices of both the urn composition and the patient allocation. The conditions on the nonhomogeneity of generating matrices are mild and widely satisfied in applications. Several applications are also discussed.

http://arXiv.org/abs/math/0503521
http://front.math.ucdavis.edu/math.PR/0503521 (alternate)

3224. A Berry-Esseen theorem for Feynman-Kac and interacting particle models

Author(s): Pierre Del Moral and Samy Tindel

Abstract: In this paper we investigate the speed of convergence of the fluctuations of a general class of Feynman-Kac particle approximation models. We design an original approach based on new Berry-Esseen type estimates for abstract martingale sequences combined with original exponential concentration estimates of interacting processes. These results extend the corresponding statements in the classical theory and apply to a class of branching and genealogical path-particle models arising in nonlinear filtering literature as well as in statistical physics and biology.

http://arXiv.org/abs/math/0503522
http://front.math.ucdavis.edu/math.PR/0503522 (alternate)

3225. Periodic copolymers at selective interfaces: A Large Deviations approach

Author(s): Erwin Bolthausen and Giambattista Giacomin

Abstract: We analyze a (1+1)-dimension directed random walk model of a polymer dipped in a medium constituted by two immiscible solvents separated by a flat interface. The polymer chain is heterogeneous in the sense that a single monomer may energetically favor one or the other solvent. We focus on the case in which the polymer types are periodically distributed along the chain or, in other words, the polymer is constituted of identical stretches of fixed length. The phenomenon that one wants to analyze is the localization at the interface: energetically favored configurations place most of the monomers in the preferred solvent and this can be done only if the polymer sticks close to the interface. We investigate, by means of large deviations, the energy-entropy competition that may lead, according to the value of the parameters (the strength of the coupling between monomers and solvents and an asymmetry parameter), to localization. We express the free energy of the system in terms of a variational formula that we can solve. We then use the result to analyze the phase diagram.

http://arXiv.org/abs/math/0503523
http://front.math.ucdavis.edu/math.PR/0503523 (alternate)

3226. Hitting distributions of geometric Brownian motion

Author(s): T. Byczkowski and M. Ryznar

Abstract: Let $\tau$ be the first hitting time of the point 1 by the geometric Brownian motion $X(t)= x \exp(B(t)-2\mu t)$ with drift $\mu \geq 0$ starting from $x>1$. Here $B(t)$ is the Brownian motion starting from 0 with $E^0 B^2(t) = 2t$. We provide an integral formula for the density function of the stopped exponential functional $A(\tau)=\int_0^\tau X^2(t) dt$ and determine its asymptotic behaviour at infinity. Although we basically rely on methods developed in \cite{BGS}, the present paper also covers the case of arbitrary drifts $\mu \geq 0$ and provides a significant unification and extension of results of the above-mentioned paper. As a corollary we provide an integral formula and give asymptotic behaviour at infinity of the Poisson kernel for half-spaces for Brownian motion with drift in real hyperbolic spaces of arbitrary dimension.

http://arXiv.org/abs/math/0503060
http://front.math.ucdavis.edu/math.PR/0503060 (alternate)

3227. Mass extinctions: an alternative to the Allee effect

Author(s): Rinaldo B. Schinazi

Abstract: We introduce a spatial stochastic process on the lattice Z^d to model mass extinctions. Each site of the lattice may host a flock of up to N individuals. Each individual may give birth to a new individual at the same site at rate \phi until the maximum of N individuals has been reached at the site. Once the flock reaches N individuals, then, and only then, it starts giving birth on each of the 2d neighboring sites at rate \lambda(N). Finally, disaster strikes at rate 1, that is, the whole flock disappears. Our model shows that, at least in theory, there is a critical maximum flock size above which a species is certain to disappear and below which it may survive.

http://arXiv.org/abs/math/0503525
http://front.math.ucdavis.edu/math.PR/0503525 (alternate)

3228. Tail of a linear diffusion with Markov switching

Author(s): Benoite de Saporta and Jian-Feng Yao

Abstract: Let Y be an Ornstein-Uhlenbeck diffusion governed by a stationary and ergodic Markov jump process X: dY_t=a(X_t)Y_t dt+\sigma(X_t) dW_t, Y_0=y_0. Ergodicity conditions for Y have been obtained. Here we investigate the tail propriety of the stationary distribution of this model. A characterization of either heavy or light tail case is established. The method is based on a renewal theorem for systems of equations with distributions on R.

http://arXiv.org/abs/math/0503527
http://front.math.ucdavis.edu/math.PR/0503527 (alternate)

3229. The long-run behavior of the stochastic replicator dynamics

Author(s): Lorens A. Imhof

Abstract: Fudenberg and Harris' stochastic version of the classical replicator dynamics is considered. The behavior of this diffusion process in the presence of an evolutionarily stable strategy is investigated. Moreover, extinction of dominated strategies and stochastic stability of strict Nash equilibria are studied. The general results are illustrated in connection with a discrete war of attrition. A persistence result for the maximum effort strategy is obtained and an explicit expression for the evolutionarily stable strategy is derived.

http://arXiv.org/abs/math/0503529
http://front.math.ucdavis.edu/math.PR/0503529 (alternate)

3230. Optimal pointwise approximation of SDEs based on brownian motion at discrete points

Author(s): Thomas Muller-Gronbach

Abstract: We study pathwise approximation of scalar stochastic differential equations at a single point. We provide the exact rate of convergence of the minimal errors that can be achieved by arbitrary numerical methods that are based (in a measurable way) on a finite number of sequential observations of the driving Brownian motion. The resulting lower error bounds hold in particular for all methods that are implementable on a computer and use a random number generator to simulate the driving Brownian motion at finitely many points. Our analysis shows that approximation at a single point is strongly connected to an integration problem for the driving Brownian motion with a random weight. Exploiting general ideas from estimation of weighted integrals of stochastic processes, we introduce an adaptive scheme, which is easy to implement and performs asymptotically optimally.

http://arXiv.org/abs/math/0503531
http://front.math.ucdavis.edu/math.PR/0503531 (alternate)

3231. Quantitative bounds on convergence of time-inhomogeneous Markov chains

Author(s): R. Douc and E. Moulines and Jeffrey S. Rosenthal

Abstract: Convergence rates of Markov chains have been widely studied in recent years. In particular, quantitative bounds on convergence rates have been studied in various forms by Meyn and Tweedie [Ann. Appl. Probab. 4 (1994) 981-1101], Rosenthal [J. Amer. Statist. Assoc. 90 (1995) 558-566], Roberts and Tweedie [Stochastic Process. Appl. 80 (1999) 211-229], Jones and Hobert [Statist. Sci. 16 (2001) 312-334] and Fort [Ph.D. thesis (2001) Univ. Paris VI]. In this paper, we extend a result of Rosenthal [J. Amer. Statist. Assoc. 90 (1995) 558-566] that concerns quantitative convergence rates for time-homogeneous Markov chains. Our extension allows us to consider f-total variation distance (instead of total variation) and time-inhomogeneous Markov chains. We apply our results to simulated annealing.

http://arXiv.org/abs/math/0503532
http://front.math.ucdavis.edu/math.PR/0503532 (alternate)

3232. On stationarity of Lagrangian observations of passive tracer velocity in a compressible environment

Author(s): Tomasz Komorowski and Grzegorz Krupa

Abstract: We study the transport of a passive tracer particle in a steady strongly mixing flow with a nonzero mean velocity. We show that there exists a probability measure under which the particle Lagrangian velocity process is stationary. This measure is absolutely continuous with respect to the underlying probability measure for the Eulerian flow.

http://arXiv.org/abs/math/0503534
http://front.math.ucdavis.edu/math.PR/0503534 (alternate)

3233. Extending Chacon-Walsh: minimality and generalised starting distributions

Author(s): Alexander Cox

Abstract: In this paper we consider the Skorokhod embedding problem for general starting and target measures. In particular, we provide necessary and sufficient conditions for a stopping time to be minimal in the sense of Monroe(1972). The resulting conditions have a nice interpretation in the graphical picture of Chacon and Walsh. Further, we demonstrate how the construction of Chacon and Walsh can be extended to any (integrable) starting and target distributions, allowing the constructions of Azema-Yor, Vallois and Jacka to be viewed in this context, and thus extended easily to general starting and target distributions. In particular, we describe in detail the extension of the Azema-Yor embedding in this context, and show that it retains its optimality property.

http://arXiv.org/abs/math/0503535
http://front.math.ucdavis.edu/math.PR/0503535 (alternate)

3234. Exponential penalty function control of loss networks

Author(s): Garud Iyengar and Karl Sigman

Abstract: We introduce penalty-function-based admission control policies to approximately maximize the expected reward rate in a loss network. These control policies are easy to implement and perform well both in the transient period as well as in steady state. A major advantage of the penalty approach is that it avoids solving the associated dynamic program. However, a disadvantage of this approach is that it requires the capacity requested by individual requests to be sufficiently small compared to total available capacity. We first solve a related deterministic linear program (LP) and then translate an optimal solution of the LP into an admission control policy for the loss network via an exponential penalty function. We show that the penalty policy is a target-tracking policy--it performs well because the optimal solution of the LP is a good target. We demonstrate that the penalty approach can be extended to track arbitrarily defined target sets. Results from preliminary simulation studies are included.

http://arXiv.org/abs/math/0503536
http://front.math.ucdavis.edu/math.PR/0503536 (alternate)

3235. Elementary bounds on Poincare and log-Sobolev constants for decomposable Markov chains

Author(s): Mark Jerrum and Jung-Bae Son and Prasad Tetali and Eric Vigoda

Abstract: We consider finite-state Markov chains that can be naturally decomposed into smaller ``projection'' and ``restriction'' chains. Possibly this decomposition will be inductive, in that the restriction chains will be smaller copies of the initial chain. We provide expressions for Poincare (resp. log-Sobolev) constants of the initial Markov chain in terms of Poincare (resp. log-Sobolev) constants of the projection and restriction chains, together with further a parameter. In the case of the Poincare constant, our bound is always at least as good as existing ones and, depending on the value of the extra parameter, may be much better. There appears to be no previously published decomposition result for the log-Sobolev constant. Our proofs are elementary and self-contained.

http://arXiv.org/abs/math/0503537
http://front.math.ucdavis.edu/math.PR/0503537 (alternate)

3236. Ruin Probabilities and Overshoots for General Levy Insurance Risk Processes

Author(s): Claudia Kluppelberg and Andreas E. Kyprianou and Ross A. Maller

Abstract: We formulate the insurance risk process in a general Levy process setting, and give general theorems for the ruin probability and the asymptotic distribution of the overshoot of the process above a high level, when the process drifts to -\infty a.s. and the positive tail of the Levy measure, or of the ladder height measure, is subexponential or, more generally, convolution equivalent. Results of Asmussen and Kluppelberg [Stochastic Process. Appl. 64 (1996) 103-125] and Bertoin and Doney [Adv. in Appl. Probab. 28 (1996) 207-226] for ruin probabilities and the overshoot in random walk and compound Poisson models are shown to have analogues in the general setup. The identities we derive open the way to further investigation of general renewal-type properties of Levy processes.

http://arXiv.org/abs/math/0503539
http://front.math.ucdavis.edu/math.PR/0503539 (alternate)

3237. Combinatorial aspects of matrix models

Author(s): Alice Guionnet and \'Edouard Maurel-Segala

Abstract: We show that under reasonably general assumptions, the first order asymptotics of the free energy of matrix models are generating functions for colored planar maps. This is based on the fact that solutions of the differential Schwinger-Dyson equations are, by nature, generating functions for enumerating planar maps, a remark which bypasses the use of Gaussian calculus.

http://arXiv.org/abs/math/0503064
http://front.math.ucdavis.edu/math.PR/0503064 (alternate)

3238. Stability in Distribution of Randomly Perturbed Quadratic Maps as Markov Processes

Author(s): Rabi Bhattacharya and Mukul Majumdar

Abstract: Iteration of randomly chosen quadratic maps defines a Markov process: X_{n+1}=\epsilon_{n+1}X_n(1-X_n), where \epsilon_n are i.i.d. with values in the parameter space [0,4] of quadratic maps F_{\theta}(x)=\theta x(1-x). Its study is of significance as an important Markov model, with applications to problems of optimization under uncertainty arising in economics. In this article a broad criterion is established for positive Harris recurrence of X_n.

http://arXiv.org/abs/math/0503540
http://front.math.ucdavis.edu/math.PR/0503540 (alternate)

3239. Interplay between dividend rate and business constraints for a financial corporation

Author(s): Tahir Choulli and Michael Taksar and Xun Yu Zhou

Abstract: We study a model of a corporation which has the possibility to choose various production/business policies with different expected profits and risks. In the model there are restrictions on the dividend distribution rates as well as restrictions on the risk the company can undertake. The objective is to maximize the expected present value of the total dividend distributions. We outline the corresponding Hamilton-Jacobi-Bellman equation, compute explicitly the optimal return function and determine the optimal policy. As a consequence of these results, the way the dividend rate and business constraints affect the optimal policy is revealed. In particular, we show that under certain relationships between the constraints and the exogenous parameters of the random processes that govern the returns, some business activities might be redundant, that is, under the optimal policy they will never be used in any scenario.

http://arXiv.org/abs/math/0503541
http://front.math.ucdavis.edu/math.PR/0503541 (alternate)

3240. Limit theorems for mixed max-sum processes with renewal stopping

Author(s): Dmitrii S. Silvestrov and Jozef L. Teugels

Abstract: This article is devoted to the investigation of limit theorems for mixed max-sum processes with renewal type stopping indexes. Limit theorems of weak convergence type are obtained as well as functional limit theorems.

http://arXiv.org/abs/math/0503543
http://front.math.ucdavis.edu/math.PR/0503543 (alternate)

3241. Continuum percolation with steps in an annulus

Author(s): Paul Balister and Bela Bollobas and Mark Walters

Abstract: Let A be the annulus in R^2 centered at the origin with inner and outer radii r(1-\epsilon) and r, respectively. Place points {x_i} in R^2 according to a Poisson process with intensity 1 and let G_A be the random graph with vertex set {x_i} and edges x_ix_j whenever x_i-x_j\in A. We show that if the area of A is large, then G_A almost surely has an infinite component. Moreover, if we fix \epsilon, increase r and let n_c=n_c(\epsilon) be the area of A when this infinite component appears, then n_c\to1 as \epsilon \to 0. This is in contrast to the case of a ``square'' annulus where we show that n_c is bounded away from 1.

http://arXiv.org/abs/math/0503544
http://front.math.ucdavis.edu/math.PR/0503544 (alternate)

3242. A microscopic probabilistic description of a locally regulated population and macroscopic approximations

Author(s): Nicolas Fournier and Sylvie Meleard

Abstract: We consider a discrete model that describes a locally regulated spatial population with mortality selection. This model was studied in parallel by Bolker and Pacala and Dieckmann, Law and Murrell. We first generalize this model by adding spatial dependence. Then we give a pathwise description in terms of Poisson point measures. We show that different normalizations may lead to different macroscopic approximations of this model. The first approximation is deterministic and gives a rigorous sense to the number density. The second approximation is a superprocess previously studied by Etheridge. Finally, we study in specific cases the long time behavior of the system and of its deterministic approximation.

http://arXiv.org/abs/math/0503546
http://front.math.ucdavis.edu/math.PR/0503546 (alternate)

3243. Stability and the Lyapounov exponent of threshold AR-ARCH Models

Author(s): Daren B. H. Cline and Huay-min H. Pu

Abstract: The Lyapounov exponent and sharp conditions for geometric ergodicity are determined of a time series model with both a threshold autoregression term and threshold autoregressive conditional heteroscedastic (ARCH) errors. The conditions require studying or simulating the behavior of a bounded, ergodic Markov chain. The method of proof is based on a new approach, called the piggyback method, that exploits the relationship between the time series and the bounded chain. The piggyback method also provides a means for evaluating the Lyapounov exponent by simulation and provides a new perspective on moments, illuminating recent results for the distribution tails of GARCH models.

http://arXiv.org/abs/math/0503547
http://front.math.ucdavis.edu/math.PR/0503547 (alternate)

3244. Normal approximation for hierarchical structures

Author(s): Larry Goldstein

Abstract: Given F:[a,b]^k\to [a,b] and a nonconstant X_0 with P(X_0\in [a,b])=1, define the hierarchical sequence of random variables {X_n}_{n\ge 0} by X_{n+1}=F(X_{n,1},...,X_{n,k}), where X_{n,i} are i.i.d. as X_n. Such sequences arise from hierarchical structures which have been extensively studied in the physics literature to model, for example, the conductivity of a random medium. Under an averaging and smoothness condition on nontrivial F, an upper bound of the form C\gamma^n for 0<\gamma<1 is obtained on the Wasserstein distance between the standardized distribution of X_n and the normal. The results apply, for instance, to random resistor networks and, introducing the notion of strict averaging, to hierarchical sequences generated by certain compositions. As an illustration, upper bounds on the rate of convergence to the normal are derived for the hierarchical sequence generated by the weighted diamond lattice which is shown to exhibit a full range of convergence rate behavior.

http://arXiv.org/abs/math/0503549
http://front.math.ucdavis.edu/math.PR/0503549 (alternate)

3245. On the super replication price of unbounded claims

Author(s): Sara Biagini and Marco Frittelli

Abstract: In an incomplete market the price of a claim f in general cannot be uniquely identified by no arbitrage arguments. However, the ``classical'' super replication price is a sensible indicator of the (maximum selling) value of the claim. When f satisfies certain pointwise conditions (e.g., f is bounded from below), the super replication price is equal to sup_QE_Q[f], where Q varies on the whole set of pricing measures. Unfortunately, this price is often too high: a typical situation is here discussed in the examples. We thus define the less expensive weak super replication price and we relax the requirements on f by asking just for ``enough'' integrability conditions. By building up a proper duality theory, we show its economic meaning and its relation with the investor's preferences. Indeed, it turns out that the weak super replication price of f coincides with sup_{Q\in M_{\Phi}}E_Q[f], where M_{\Phi} is the class of pricing measures with finite generalized entropy (i.e., E[\Phi (\frac{dQ}{dP})]<\infty) and where \Phi is the convex conjugate of the utility function of the investor.

http://arXiv.org/abs/math/0503550
http://front.math.ucdavis.edu/math.PR/0503550 (alternate)

3246. Limit laws of estimators for critical multi-type Galton-Watson processes

Author(s): Zhiyi Chi

Abstract: We consider the asymptotics of various estimators based on a large sample of branching trees from a critical multi-type Galton-Watson process, as the sample size increases to infinity. The asymptotics of additive functions of trees, such as sizes of trees and frequencies of types within trees, a higher-order asymptotic of the ``relative frequency'' estimator of the left eigenvector of the mean matrix, a higher-order joint asymptotic of the maximum likelihood estimators of the offspring probabilities and the consistency of an estimator of the right eigenvector of the mean matrix, are established.

http://arXiv.org/abs/math/0503552
http://front.math.ucdavis.edu/math.PR/0503552 (alternate)

3247. On Sampling of stationary increment processes

Author(s): J. M. P. Albin

Abstract: Under a complex technical condition, similar to such used in extreme value theory, we find the rate q(\epsilon)^{-1} at which a stochastic process with stationary increments \xi should be sampled, for the sampled process \xi(\lfloor\cdot /q(\epsilon)\rfloor q(\epsilon)) to deviate from \xi by at most \epsilon, with a given probability, asymptotically as \epsilon \downarrow0. The canonical application is to discretization errors in computer simulation of stochastic processes.

http://arXiv.org/abs/math/0503554
http://front.math.ucdavis.edu/math.PR/0503554 (alternate)

3248. Recurrence of Simple Random Walk on $Z^2$ is Dynamically Sensitive

Author(s): Christopher Hoffman

Abstract: Benjamini, Haggstrom, Peres and Steif introduced the concept of a dynamical random walk. This is a continuous family of random walks, {S_n(t)}. Benjamini et. al. proved that if d=3 or d=4 then there is an exceptional set of t such that {S_n(t)} returns to the origin infinitely often. In this paper we consider a dynamical random walk on Z^2. We show that with probability one there exists t such that {S_n(t)} never returns to the origin. This exceptional set of times has dimension one. This proves a conjecture of Benjamini et. al.

http://arXiv.org/abs/math/0503065
http://front.math.ucdavis.edu/math.PR/0503065 (alternate)

3249. Spectral properties of the tandem Jackson network, seen as a quasi-birth-and-death process

Author(s): D. P. Kroese and W. R. W. Scheinhardt and P. G. Taylor

Abstract: Quasi-birth-and-death (QBD) processes with infinite ``phase spaces'' can exhibit unusual and interesting behavior. One of the simplest examples of such a process is the two-node tandem Jackson network, with the ``phase'' giving the state of the first queue and the ``level'' giving the state of the second queue. In this paper, we undertake an extensive analysis of the properties of this QBD. In particular, we investigate the spectral properties of Neuts's R-matrix and show that the decay rate of the stationary distribution of the ``level'' process is not always equal to the convergence norm of R. In fact, we show that we can obtain any decay rate from a certain range by controlling only the transition structure at level zero, which is independent of R. We also consider the sequence of tandem queues that is constructed by restricting the waiting room of the first queue to some finite capacity, and then allowing this capacity to increase to infinity. We show that the decay rates for the finite truncations converge to a value, which is not necessarily the decay rate in the infinite waiting room case. Finally, we show that the probability that the process hits level n before level 0 given that it starts in level 1 decays at a rate which is not necessarily the same as the decay rate for the stationary distribution.

http://arXiv.org/abs/math/0503555
http://front.math.ucdavis.edu/math.PR/0503555 (alternate)

3250. Number of paths versus number of basis functions in American option pricing

Author(s): Paul Glasserman and Bin Yu

Abstract: An American option grants the holder the right to select the time at which to exercise the option, so pricing an American option entails solving an optimal stopping problem. Difficulties in applying standard numerical methods to complex pricing problems have motivated the development of techniques that combine Monte Carlo simulation with dynamic programming. One class of methods approximates the option value at each time using a linear combination of basis functions, and combines Monte Carlo with backward induction to estimate optimal coefficients in each approximation. We analyze the convergence of such a method as both the number of basis functions and the number of simulated paths increase. We get explicit results when the basis functions are polynomials and the underlying process is either Brownian motion or geometric Brownian motion. We show that the number of paths required for worst-case convergence grows exponentially in the degree of the approximating polynomials in the case of Brownian motion and faster in the case of geometric Brownian motion.

http://arXiv.org/abs/math/0503556
http://front.math.ucdavis.edu/math.PR/0503556 (alternate)

3251. Stochastic Characterization of Harmonic maps on Riemannian polyhedra

Author(s): M. A. Aprodu and T. Bouziane

Abstract: The aim of this paper is to relate the theory of Harmonicity in sense Korevaar-Schoen and Eells-Fuglede to the notion of a Brownian motion in riemannian polyhedra achieved by the second author. Firstly, we prove that Brownian motions is stochastically continuous Markov processes and consequently it has a unique infinitesimal generator on some Banach space. Secondly, we show that in some sense, the Brownian motion in Riemannian polyhedra has as an infinitesimal generator the "Laplacian". Finally, we show that harmonic maps, with target smooth Riemannian manifolds, in the sense of Eells-Fuglede, are exactly those which maps Brownian motion in Riemannian polyhedron into a martingale, while harmonic morphisms are exactly the maps which are Brownian preserving paths

http://arXiv.org/abs/math/0503557
http://front.math.ucdavis.edu/math.PR/0503557 (alternate)

3252. Central limit theorems for random polytopes in a smooth convex set

Author(s): Van Vu

Abstract: Let $K$ be a smooth convex set with volume one in $\BBR^d$. Choose $n$ random points in $K$ independently according to the uniform distribution. The convex hull of these points, denoted by $K_n$, is called a {\it random polytope}. We prove that several key functionals of $K_n$ satisfy the central limit theorem as $n$ tends to infinity.

http://arXiv.org/abs/math/0503559
http://front.math.ucdavis.edu/math.PR/0503559 (alternate)

3253. Quenched invariance principle for simple random walk on two-dimensional percolation clusters

Author(s): Noam Berger and Marek Biskup

Abstract: We consider the simple random walk on a two-dimensional super-critical infinite percolation cluster and prove that for almost every configuration it scales to Brownian motion.

http://arXiv.org/abs/math/0503576
http://front.math.ucdavis.edu/math.PR/0503576 (alternate)

3254. Asymptotic genealogy of a critical branching process

Author(s): Lea Popovic

Abstract: Consider a continuous-time binary branching process conditioned to have population size n at some time t, and with a chance p for recording each extinct individual in the process. Within the family tree of this process, we consider the smallest subtree containing the genealogy of the extant individuals together with the genealogy of the recorded extinct individuals. We introduce a novel representation of such subtrees in terms of a point-process, and provide asymptotic results on the distribution of this point-process as the number of extant individuals increases. We motivate the study within the scope of a coherent analysis for an a priori model for macroevolution.

http://arXiv.org/abs/math/0503577
http://front.math.ucdavis.edu/math.PR/0503577 (alternate)

3255. Generalized stochastic differential utility and preference for information

Author(s): Ali Lazrak

Abstract: This paper develops, in a Brownian information setting, an approach for analyzing the preference for information, a question that motivates the stochastic differential utility (SDU) due to Duffie and Epstein [Econometrica 60 (1992) 353-394]. For a class of backward stochastic differential equations (BSDEs) including the generalized SDU [Lazrak and Quenez Math. Oper. Res. 28 (2003) 154-180], we formulate the information neutrality property as an invariance principle when the filtration is coarser (or finer) and characterize it. We also provide concrete examples of heterogeneity in information that illustrate explicitly the nonneutrality property for some GSDUs. Our results suggest that, within the GSDUs class of intertemporal utilities, risk aversion or ambiguity aversion are inflexibly linked to the preference for information.

http://arXiv.org/abs/math/0503579
http://front.math.ucdavis.edu/math.PR/0503579 (alternate)

3256. The right time to sell a stock whose price is driven by Markovian noise

Author(s): Robert C. Dalang and M.-O. Hongler

Abstract: We consider the problem of finding the optimal time to sell a stock, subject to a fixed sales cost and an exponential discounting rate \rho. We assume that the price of the stock fluctuates according to the equation dY_t=Y_t(\mu dt+\sigma\xi(t) dt), where (\xi(t)) is an alternating Markov renewal process with values in {\pm1}, with an exponential renewal time. We determine the critical value of \rho under which the value function is finite. We examine the validity of the ``principle of smooth fit'' and use this to give a complete and essentially explicit solution to the problem, which exhibits a surprisingly rich structure. The corresponding result when the stock price evolves according to the Black and Scholes model is obtained as a limit case.

http://arXiv.org/abs/math/0503580
http://front.math.ucdavis.edu/math.PR/0503580 (alternate)

3257. Concentration of normalized sums and a central limit theorem for noncorrelated random variables

Author(s): Sergey G. Bobkov

Abstract: For noncorrelated random variables, we study a concentration property of the family of distributions of normalized sums formed by sequences of times of a given large length.

http://arXiv.org/abs/math/0503583
http://front.math.ucdavis.edu/math.PR/0503583 (alternate)

3258. Analysis of a Class of Likelihood Based Continuous Time Stochastic Volatility Models including Ornstein-Uhlenbeck Models in Financial Economics

Author(s): Lancelot F. James

Abstract: In a series of recent papers Barndorff-Nielsen and Shephard introduce an attractive class of continuous time stochastic volatility models for financial assets where the volatility processes are functions of positive Ornstein-Uhlenbeck(OU) processes. This models are known to be substantially more flexible than Gaussian based models. One current problem of this approach is the unavailability of a tractable exact analysis of likelihood based stochastic volatility models for the returns of log prices of stocks. With this point in mind, the likelihood models of Barndorff-Nielsen and Shephard are viewed as members of a much larger class of models. That is likelihoods based on n conditionally independent Normal random variables whose mean and variance are representable as linear functionals of a common unobserved Poisson random measure. The analysis of these models is facilitated by applying the methods in James (2005, 2002), in particular an Esscher type transform of Poisson random measures; in conjunction with a special case of the Weber-Sonine formula. It is shown that the marginal likelihood may be expressed in terms of a multidimensional Fourier-cosine transform. This yields tractable forms of the likelihood and also allows a full Bayesian posterior analysis of the integrated volatility process. A general formula for the posterior density of the log price given the observed data is derived, which could potentially have applications to option pricing. We also identify tractable subclasses, where inference can be based on a finite number of independent random variables. It is shown that inference does not necessarily require simulation of random measures. Rather, classical numerical integration can be used in the most general cases.

http://arXiv.org/abs/math/0503055
http://front.math.ucdavis.edu/math.ST/0503055 (alternate)

3259. Modified logarithmic Sobolev inequalities in null curvature

Author(s): Ivan Gentil and Arnaud Guillin and Laurent Miclo

Abstract: We present a logarithmic Sobolev inequality adapted to a log-concave measure. Assume that $\Phi$ is a symmetric convex function on $\dR$ satisfying $(1+\e)\Phi(x)\leq {x}\Phi'(x)\leq(2-\e)\Phi(x)$ for $x\geq0$ large enough and with $\e\in]0,1/2]$. We prove that the probability measure on $\dR$ $\mu_\Phi(dx)=e^{-\Phi(x)}/Z_\Phi dx$ satisfies a modified and adapted logarithmic Sobolev inequality : there exist three constant $A,B,D>0$ such that for all smooth $f>0$, \begin{equation*} \ent{\mu_\Phi}{f^2}\leq A\int H_{\Phi}\PAR{{\frac{f'}{f}}}f^2d\mu_\Phi, \text{with} H_{\Phi}(x)= {\begin{array}{rl} \Phi^*\PAR{Bx} &\text{if }\ABS{x}\geq D, x^2 &\text{if}\ABS{x}\leq D. \end{array} . \end{equation*}

http://arXiv.org/abs/math/0503585
http://front.math.ucdavis.edu/math.PR/0503585 (alternate)

3260. Lenses in Skew Brownian Flow

Author(s): Krzysztof Burdzy and Haya Kaspi

Abstract: We consider a stochastic flow in which individual particles follow skew Brownian motions, with each one of these processes driven by the same Brownian motion. One does not have uniqueness for the solutions of the corresponding stochastic differential equation simultaneously for all real initial conditions. Due to this lack of the simultaneous strong uniqueness for the whole system of stochastic differential equations, the flow contains lenses, that is, pairs of skew Brownian motions which start at the same point, bifurcate, and then coalesce in a finite time. The paper contains qualitative and quantitative (distributional) results on the geometry of the flow and lenses.

http://arXiv.org/abs/math/0503586
http://front.math.ucdavis.edu/math.PR/0503586 (alternate)

3261. Weak Poincare inequalities on domains defined by Brownian rough paths

Author(s): Shigeki Aida

Abstract: We prove weak Poincare inequalities on domains which are inverse images of open sets in Wiener spaces under continuous functions of Brownian rough paths. The result is applicable to Dirichlet forms on loop groups and connected open subsets of path spaces over compact Riemannian manifolds.

http://arXiv.org/abs/math/0503587
http://front.math.ucdavis.edu/math.PR/0503587 (alternate)

3262. Time changes of symmetric diffusions and Feller measures

Author(s): Masatoshi Fukushima and Ping He and Jiangang Ying

Abstract: We extend the classical Douglas integral, which expresses the Dirichlet integral of a harmonic function on the unit disk in terms of its value on boundary, to the case of conservative symmetric diffusion in terms of Feller measure, by using the approach of time change of Markov processes.

http://arXiv.org/abs/math/0503588
http://front.math.ucdavis.edu/math.PR/0503588 (alternate)

3263. Difference prophet inequalities for [0,1]-valued i.i.d. random variables with cost for observations

Author(s): Holger Kosters

Abstract: Let X_1,X_2,... be a sequence of [0,1]-valued i.i.d. random variables, let c\geq 0 be a sampling cost for each observation and let Y_i=X_i-ic, i=1,2,.... For n=1,2,..., let M(Y_1,...,Y_n)=E(max_{1\leq i\leq n}Y_i) and V(Y_1,...,Y_n)=sup_{\tau \in C^n}E(Y_{\tau}), where C^n denotes the set of all stopping rules for Y_1,...,Y_n. Sharp upper bounds for the difference M(Y_1,...,Y_n)-V(Y_1,...,Y_n) are given under various restrictions on c and n.

http://arXiv.org/abs/math/0503589
http://front.math.ucdavis.edu/math.PR/0503589 (alternate)

3264. Uniqueness for diffusions degenerating at the boundary of a smooth bounded set

Author(s): Dante DeBlassie

Abstract: For continuous \gamma, g:[0,1]\to(0,\infty), consider the degenerate stochastic differential equation dX_t=[1-|X_t|^2]^{1/2}\gamma(|X_t|) dB_t-g(|X_t|)X_t dt in the closed unit ball of R^n. We introduce a new idea to show pathwise uniqueness holds when \gamma and g are Lipschitz and \frac{g(1)}{\gamma^2(1)}>\sqrt2-1. When specialized to a case studied by Swart [Stochastic Process. Appl. 98 (2002) 131-149] with \gamma=\sqrt2 and g\equiv c, this gives an improvement of his result. Our method applies to more general contexts as well. Let D be a bounded open set with C^3 boundary and suppose h:\barD\to R Lipschitz on \barD, as well as C^2 on a neighborhood of \partial D with Lipschitz second partials there. Also assume h>0 on D, h=0 on \partial D and |\nabla h|>0 on \partial D. An example of such a function is h(x)=d(x,\partial D). We give conditions which ensure pathwise uniqueness holds for dX_t=h(X_t)^{1/2}\sigma(X_t) dB_t+b(X_t) dt in \barD.

http://arXiv.org/abs/math/0503590
http://front.math.ucdavis.edu/math.PR/0503590 (alternate)

3265. Moderate deviations for diffusions with Brownian potentials

Author(s): Yueyun Hu and Zhan Shi

Abstract: We present precise moderate deviation probabilities, in both quenched and annealed settings, for a recurrent diffusion process with a Brownian potential. Our method relies on fine tools in stochastic calculus, including Kotani's lemma and Lamperti's representation for exponential functionals. In particular, our result for quenched moderate deviations is in agreement with a recent theorem of Comets and Popov [Probab. Theory Related Fields 126 (2003) 571-609] who studied the corresponding problem for Sinai's random walk in random environment.

http://arXiv.org/abs/math/0503591
http://front.math.ucdavis.edu/math.PR/0503591 (alternate)

3266. Self-intersection local time: Critical exponent, large deviations, and laws of the iterated logarithm

Author(s): Richard F. Bass and Xia Chen

Abstract: If \beta_t is renormalized self-intersection local time for planar Brownian motion, we characterize when Ee^{\gamma\beta_1} is finite or infinite in terms of the best constant of a Gagliardo-Nirenberg inequality. We prove large deviation estimates for \beta_1 and -\beta_1. We establish lim sup and lim inf laws of the iterated logarithm for \beta_t as t\to\infty.

http://arXiv.org/abs/math/0503592
http://front.math.ucdavis.edu/math.PR/0503592 (alternate)

3267. Exponential asymptotics and law of the iterated logarithm for intersection local times of random walks

Author(s): Xia Chen

Abstract: Let \alpha ([0,1]^p) denote the intersection local time of p independent d-dimensional Brownian motions running up to the time 1. Under the conditions p(d-2)

http://arXiv.org/abs/math/0503593
http://front.math.ucdavis.edu/math.PR/0503593 (alternate)

3268. Regularity of solutions to stochastic Volterra equations with infinite delay

Author(s): Anna Karczewska and Carlos Lizama

Abstract: The paper gives necessary and sufficient conditions providing regularity of solutions to stochastic Volterra equations with infinite delay on a $d$-dimensional torus. The harmonic analysis techniques and stochastic integration in function spaces are used.

http://arXiv.org/abs/math/0503595
http://front.math.ucdavis.edu/math.PR/0503595 (alternate)

3269. A Class of Generalized Hyperbolic Continuous Time Integrated Stochastic Volatility Likelihood Models

Author(s): Lancelot F. James and John W. Lau

Abstract: This paper discusses and analyzes a class of likelihood models which are based on two distributional innovations in financial models for stock returns. That is, the notion that the marginal distribution of aggregate returns of log-stock prices are well approximated by generalized hyperbolic distributions, and that volatility clustering can be handled by specifying the integrated volatility as a random process such as that proposed in a recent series of papers by Barndorff-Nielsen and Shephard (BNS). The BNS models produce likelihoods for aggregate returns which can be viewed as a subclass of latent regression models where one has n conditionally independent Normal random variables whose mean and variance are representable as linear functionals of a common unobserved Poisson random measure. James (2005b) recently obtains an exact analysis for such models yielding expressions of the likelihood in terms of quite tractable Fourier-Cosine integrals. Here, our idea is to analyze a class of likelihoods, which can be used for similar purposes, but where the latent regression models are based on n conditionally independent models with distributions belonging to a subclass of the generalized hyperbolic distributions and whose corresponding parameters are representable as linear functionals of a common unobserved Poisson random measure. Our models are perhaps most closely related to the Normal inverse Gaussian/GARCH/A-PARCH models of Brandorff-Nielsen (1997) and Jensen and Lunde (2001), where in our case the GARCH component is replaced by quantities such as INT-OU processes. It is seen that, importantly, such likelihood models exhibit quite different features structurally. One nice feature of the model is that it allows for more flexibility in terms of modelling of external regression parameters.

http://arXiv.org/abs/math/0503056
http://front.math.ucdavis.edu/math.ST/0503056 (alternate)

3270. A Local limit theorem for directed polymers in random media: the continuous and the discrete case

Author(s): Vincent Vargas (PMA)

Abstract: In this article, we consider two models of directed polymers in random environment: a discrete model and a continuous model. We consider these models in dimension greater or equal to 3 and we suppose that the normalized partition function is bounded in L^2. Under these assumptions, Sinai proved a local limit theorem for the discrete model, using a perturbation expansion. In this article, we give a new method for proving Sinai's local limit theorem. This new method can be transposed to the continuous setting in which we prove a similar local limit theorem.

http://arXiv.org/abs/math/0503596
http://front.math.ucdavis.edu/math.PR/0503596 (alternate)

3271. Global L_2-solutions of stochastic Navier-Stokes equations

Author(s): R. Mikulevicius and B. L. Rozovskii

Abstract: This paper concerns the Cauchy problem in R^d for the stochastic Navier-Stokes equation \partial_tu=\Delta u-(u,\nabla)u-\nabla p+f(u)+ [(\sigma,\nabla)u-\nabla \tilde p+g(u)]\circ \dot W, u(0)=u_0,\qquad divu=0, driven by white noise \dot W. Under minimal assumptions on regularity of the coefficients and random forces, the existence of a global weak (martingale) solution of the stochastic Navier-Stokes equation is proved. In the two-dimensional case, the existence and pathwise uniqueness of a global strong solution is shown. A Wiener chaos-based criterion for the existence and uniqueness of a strong global solution of the Navier-Stokes equations is established.

http://arXiv.org/abs/math/0503597
http://front.math.ucdavis.edu/math.PR/0503597 (alternate)

3272. Central limit theorems for sequences of multiple stochastic integrals

Author(s): David Nualart and Giovanni Peccati

Abstract: We characterize the convergence in distribution to a standard normal law for a sequence of multiple stochastic integrals of a fixed order with variance converging to 1. Some applications are given, in particular to study the limiting behavior of quadratic functionals of Gaussian processes.

http://arXiv.org/abs/math/0503598
http://front.math.ucdavis.edu/math.PR/0503598 (alternate)

3273. Stochastic integral representation and regularity of the density for the Exit measure of super-Brownian motion

Author(s): Jean-Francois Le Gall and Leonid Mytnik

Abstract: This paper studies the regularity properties of the density of the exit measure for super-Brownian motion with (1+\beta)-stable branching mechanism. It establishes the continuity of the density in dimension d=2 and the unboundedness of the density in all other dimensions where the density exists. An alternative description of the exit measure and its density is also given via a stochastic integral representation. Results are applied to the probabilistic representation of nonnegative solutions of the partial differential equation \Delta u=u^{1+\beta}.

http://arXiv.org/abs/math/0503599
http://front.math.ucdavis.edu/math.PR/0503599 (alternate)

3274. Precise asymptotics of small eigenvalues of reversible diffusions in the metastable regime

Author(s): Michael Eckhoff

Abstract: We investigate the close connection between metastability of the reversible diffusion process X defined by the stochastic differential equation dX_t=-\nabla F(X_t) dt+\sqrt2\epsilon dW_t,\qquad \epsilon >0, and the spectrum near zero of its generator -L_{\epsilon}\equiv \epsilon \Delta -\nabla F\cdot\nabla, where F:R^d\to R and W denotes Brownian motion on R^d. For generic F to each local minimum of F there corresponds a metastable state. We prove that the distribution of its rescaled relaxation time converges to the exponential distribution as \epsilon \downarrow 0 with optimal and uniform error estimates. Each metastable state can be viewed as an eigenstate of L_{\epsilon} with eigenvalue which converges to zero exponentially fast in 1/\epsilon. Modulo errors of exponentially small order in 1/\epsilon this eigenvalue is given as the inverse of the expected metastable relaxation time. The eigenstate is highly concentrated in the basin of attraction of the corresponding trap.

http://arXiv.org/abs/math/0503600
http://front.math.ucdavis.edu/math.PR/0503600 (alternate)

3275. Asymptotic expansions for the Laplace approximations of sums of Banach space-valued random variables

Author(s): Sergio Albeverio and Song Liang

Abstract: Let X_i, i\in N, be i.i.d. B-valued random variables, where B is a real separable Banach space. Let \Phi be a smooth enough mapping from B into R. An asymptotic evaluation of Z_n=E(\exp (n\Phi (\sum_{i=1}^nX_i/n))), up to a factor (1+o(1)), has been gotten in Bolthausen [Probab. Theory Related Fields 72 (1986) 305-318] and Kusuoka and Liang [Probab. Theory Related Fields 116 (2000) 221-238]. In this paper, a detailed asymptotic expansion of Z_n as n\to \infty is given, valid to all orders, and with control on remainders. The results are new even in finite dimensions.

http://arXiv.org/abs/math/0503601
http://front.math.ucdavis.edu/math.PR/0503601 (alternate)

3276. Multiplicative monotone convolutions

Author(s): Uwe Franz

Abstract: Recently, Bercovici has introduced multiplicative convolutions based on Muraki's monotone independence and shown that these convolution of probability measures correspond to the composition of some function of their Cauchy transforms. We provide a new proof of this fact based on the combinatorics of moments. We also give a new characterisation of the probability measures that can be embedded into continuous monotone convolution semigroups of probability measures on the unit circle and briefly discuss a relation to Galton-Watson processes.

http://arXiv.org/abs/math/0503602
http://front.math.ucdavis.edu/math.PR/0503602 (alternate)

3277. Extremes on Trees

Author(s): Tailen Hsing and Holger Rootzen

Abstract: This paper considers the asymptotic distribution of the longest edge of the minimal spanning tree and nearest neighbor graph on X_1,...,X_{N_n} where X_1,X_2,... are i.i.d. in \Re^2 with distribution F and N_n is independent of the X_i and satisfies N_n/n\to_p1. A new approach based on spatial blocking and a locally orthogonal coordinate system is developed to treat cases for which F has unbounded support. The general results are applied to a number of special cases, including elliptically contoured distributions, distributions with independent Weibull-like margins and distributions with parallel level curves.

http://arXiv.org/abs/math/0503603
http://front.math.ucdavis.edu/math.PR/0503603 (alternate)

3278. On the monotonicity of the speed of random walks on a percolation cluster of trees

Author(s): Dayue Chen and Fuxi Zhang

Abstract: We consider the simple random walk on the infinite cluster of the Bernoulli bond percolation of trees, and investigate the relation between the speed of the simple random walk and the retaining probability $p$ by studying three classes of trees. A sufficient condition is established for Galton-Watson trees.

http://arXiv.org/abs/math/0503610
http://front.math.ucdavis.edu/math.PR/0503610 (alternate)

3279. Contractive Markov systems II

Author(s): Ivan Werner

Abstract: In this paper, we continue development of the theory of contractive Markov systems (CMSs) initiated in \cite{Wer1}. We extend some results from \cite{Wer1}, \cite{Wer3}, \cite{Wer5} and \cite{Wer6} to the case of contractive Markov systems with probabilities which have a square summable variation by using some ideas of A. Johansson and A. Oeberg \cite{JO}. In particular, we show that an irreducible CMS has a unique invariant Borel probability measure if the vertex sets form an open partition of the state space and the restrictions of the probability functions on their vertex sets have a square summable variation and are bounded away from zero.

http://arXiv.org/abs/math/0503633
http://front.math.ucdavis.edu/math.PR/0503633 (alternate)

3280. Limit theorems for iterated random topical operators

Author(s): Glenn Merlet (IRMAR)

Abstract: Let A(n) be a sequence of i.i.d. topical (i.e. isotone and additively homogeneous) operators. Let $x(n,x\_0)$ be defined by $x(0,x\_0)=x\_0$ and $x(n,x\_0)=A(n)x(n-1,x\_0)$. This can modelize a wide range of systems including, task graphs, train networks, Job-Shop, timed digital circuits or parallel processing systems. When A(n) has the memory loss property, we use the spectral gap method to prove limit theorems for $x(n,x\_0)$. Roughly speaking, we show that $x(n,x\_0)$ behaves like a sum of i.i.d. real variables. Precisely, we show that with suitable additional conditions, it satisfies a central limit theorem with rate, a local limit theorem, a renewal theorem and a large deviations principle, and we give an algebraic condition to ensure the positivity of the variance in the CLT. When A(n) are defined by matrices in the \mp semi-ring, we give more effective statements and show that the additional conditions and the positivity of the variance in the CLT are generic.

http://arXiv.org/abs/math/0503634
http://front.math.ucdavis.edu/math.PR/0503634 (alternate)

3281. A probabilistic approach to the geometry of the \ell_p^n-ball

Author(s): Franck Barthe and Olivier Guedon and Shahar Mendelson and Assaf Naor

Abstract: This article investigates, by probabilistic methods, various geometric questions on B_p^n, the unit ball of \ell_p^n. We propose realizations in terms of independent random variables of several distributions on B_p^n, including the normalized volume measure. These representations allow us to unify and extend the known results of the sub-independence of coordinate slabs in B_p^n. As another application, we compute moments of linear functionals on B_p^n, which gives sharp constants in Khinchine's inequalities on B_p^n and determines the \psi_2-constant of all directions on B_p^n. We also study the extremal values of several Gaussian averages on sections of B_p^n (including mean width and \ell-norm), and derive several monotonicity results as p varies. Applications to balancing vectors in \ell_2 and to covering numbers of polyhedra complete the exposition.

http://arXiv.org/abs/math/0503650
http://front.math.ucdavis.edu/math.PR/0503650 (alternate)

3282. Moment inequalities for functions of independent random variables

Author(s): Stephane Boucheron and Olivier Bousquet and Gabor Lugosi and Pascal Massart

Abstract: A general method for obtaining moment inequalities for functions of independent random variables is presented. It is a generalization of the entropy method which has been used to derive concentration inequalities for such functions [Boucheron, Lugosi and Massart Ann. Probab. 31 (2003) 1583-1614], and is based on a generalized tensorization inequality due to Latala and Oleszkiewicz [Lecture Notes in Math. 1745 (2000) 147-168]. The new inequalities prove to be a versatile tool in a wide range of applications. We illustrate the power of the method by showing how it can be used to effortlessly re-derive classical inequalities including Rosenthal and Kahane-Khinchine-type inequalities for sums of independent random variables, moment inequalities for suprema of empirical processes and moment inequalities for Rademacher chaos and U-statistics. Some of these corollaries are apparently new. In particular, we generalize Talagrand's exponential inequality for Rademacher chaos of order 2 to any order. We also discuss applications for other complex functions of independent random variables, such as suprema of Boolean polynomials which include, as special cases, subgraph counting problems in random graphs.

http://arXiv.org/abs/math/0503651
http://front.math.ucdavis.edu/math.PR/0503651 (alternate)

3283. On the stochastic calculus method for spins systems

Author(s): Samy Tindel

Abstract: In this note we show how to generalize the stochastic calculus method introduced by Comets and Neveu [Comm. Math. Phys. 166 (1995) 549-564] for two models of spin glasses, namely, the SK model with external field and the perceptron model. This method allows to derive quite easily some fluctuation results for the free energy in those two cases.

http://arXiv.org/abs/math/0503652
http://front.math.ucdavis.edu/math.PR/0503652 (alternate)

3284. Closures of exponential families

Author(s): Imre Csiszar and Frantisek Matus

Abstract: The variation distance closure of an exponential family with a convex set of canonical parameters is described, assuming no regularity conditions. The tools are the concepts of convex core of a measure and extension of an exponential family, introduced previously by the authors, and a new concept of accessible faces of a convex set. Two other closures related to the information divergence are also characterized.

http://arXiv.org/abs/math/0503653
http://front.math.ucdavis.edu/math.PR/0503653 (alternate)

3285. One-dependent trigonometric determinantal processes are two-block-factors

Author(s): Erik I. Broman

Abstract: Given a trigonometric polynomial f:[0,1]\to[0,1] of degree m, one can define a corresponding stationary process {X_i}_{i\in Z} via determinants of the Toeplitz matrix for f. We show that for m=1 this process, which is trivially one-dependent, is a two-block-factor.

http://arXiv.org/abs/math/0503654
http://front.math.ucdavis.edu/math.PR/0503654 (alternate)

3286. Asymptotics for hitting times

Author(s): M. Kupsa and Y. Lacroix

Abstract: In this paper we characterize possible asymptotics for hitting times in aperiodic ergodic dynamical systems: asymptotics are proved to be the distribution functions of subprobability measures on the line belonging to the functional class {6pt} {-3mm}(A){6mm}F={F:R\to [0,1]:\left\lbrack \matrixF is increasing, null on ]-\infty, 0]; \noalignF is continuous and concave; \noalignF(t)\le t for t\ge 0.\right.}. {6pt} Note that all possible asymptotics are absolutely continuous.

http://arXiv.org/abs/math/0503655
http://front.math.ucdavis.edu/math.PR/0503655 (alternate)

3287. Krein's spectral theory and the Paley-Wiener expansion for fractional Brownian motion

Author(s): Kacha Dzhaparidze and Harry van Zanten

Abstract: In this paper we develop the spectral theory of the fractional Brownian motion (fBm) using the ideas of Krein's work on continuous analogous of orthogonal polynomials on the unit circle. We exhibit the functions which are orthogonal with respect to the spectral measure of the fBm and obtain an explicit reproducing kernel in the frequency domain. We use these results to derive an extension of the classical Paley-Wiener expansion of the ordinary Brownian motion to the fractional case.

http://arXiv.org/abs/math/0503656
http://front.math.ucdavis.edu/math.PR/0503656 (alternate)

3288. Criticality for branching processes in random environment

Author(s): V. I. Afanasyev and J. Geiger and G. Kersting and V. A. Vatutin

Abstract: We study branching processes in an i.i.d. random environment, where the associated random walk is of the oscillating type. This class of processes generalizes the classical notion of criticality. The main properties of such branching processes are developed under a general assumption, known as Spitzer's condition in fluctuation theory of random walks, and some additional moment condition. We determine the exact asymptotic behavior of the survival probability and prove conditional functional limit theorems for the generation size process and the associated random walk. The results rely on a stimulating interplay between branching process theory and fluctuation theory of random walks.

http://arXiv.org/abs/math/0503657
http://front.math.ucdavis.edu/math.PR/0503657 (alternate)

3289. Examples of moderate deviation principle for diffusion processes

Author(s): A. Guillin} and R. Liptser

Abstract: Taking into account some likeness of moderate deviations (MD) and central limit theorems (CLT), we develop an approach, which made a good showing in CLT, for MD analysis of a family $$ S^\kappa_t=\frac{1}{t^\kappa}\int_0^tH(X_s)ds, \ t\to\infty $$ for an ergodic diffusion process $X_t$ under $0.5<\kappa<1$ and appropriate $H$. We mean a decomposition with ``corrector'': $$ \frac{1}{t^\kappa}\int_0^tH(X_s)ds={\rm corrector}+\frac{1}{t^\kappa}\underbrace{M_t}_{\rm martingale}. $$ and show that, as in the CLT analysis, the corrector is negligible but in the MD scale, and the main contribution in the MD brings the family ``$ \frac{1}{t^\kappa}M_t, t\to\infty. $'' Starting from Bayer and Freidlin, \cite{BF}, and finishing by Wu's papers \cite{Wu1}-\cite{WuH}, in the MD study Laplace's transform dominates. In the paper, we replace the Laplace technique by one, admitting to give the conditions, providing the MD, in terms of ``drift-diffusion'' parameters and $H$. However, a verification of these conditions heavily depends on a specificity of a diffusion model. That is why the paper is named ``Examples ...''.

http://arXiv.org/abs/math/0503070
http://front.math.ucdavis.edu/math.PR/0503070 (alternate)

3290. Confidence intervals for nonhomogeneous branching processes and polymerase chain reactions

Author(s): Didier Piau

Abstract: We extend in two directions our previous results about the sampling and the empirical measures of immortal branching Markov processes. Direct applications to molecular biology are rigorous estimates of the mutation rates of polymerase chain reactions from uniform samples of the population after the reaction. First, we consider nonhomogeneous processes, which are more adapted to real reactions. Second, recalling that the first moment estimator is analytically known only in the infinite population limit, we provide rigorous confidence intervals for this estimator that are valid for any finite population. Our bounds are explicit, nonasymptotic and valid for a wide class of nonhomogeneous branching Markov processes that we describe in detail. In the setting of polymerase chain reactions, our results imply that enlarging the size of the sample becomes useless for surprisingly small sizes. Establishing confidence intervals requires precise estimates of the second moment of random samples. The proof of these estimates is more involved than the proofs that allowed us, in a previous paper, to deal with the first moment. On the other hand, our method uses various, seemingly new, monotonicity properties of the harmonic moments of sums of exchangeable random variables.

http://arXiv.org/abs/math/0503659
http://front.math.ucdavis.edu/math.PR/0503659 (alternate)

3291. Sectorial convergence of U-statistics

Author(s): Anda Gadidov

Abstract: In this note we show that almost sure convergence to zero of symmetrized U-statistics indexed by a linear sector in Z^d_+ is equivalent to convergence along the diagonal of Z^d_+, as it is considered in Lata\la and Zinn [Ann. Probab. 28 (2000) 1908-1924]. Comparisons with similar results for sums of multi-indexed i.i.d. random variables are also made.

http://arXiv.org/abs/math/0503660
http://front.math.ucdavis.edu/math.PR/0503660 (alternate)

3292. A strong invariance principle for associated random fields

Author(s): Raluca M. Balan

Abstract: In this paper we generalize Yu's [Ann. Probab. 24 (1996) 2079-2097] strong invariance principle for associated sequences to the multi-parameter case, under the assumption that the covariance coefficient u(n) decays exponentially as n\to \infty. The main tools that we use are the following: the Berkes and Morrow [Z. Wahrsch. Verw. Gebiete 57 (1981) 15-37] multi-parameter blocking technique, the Csorgo and Revesz [Z. Wahrsch. Verw. Gebiete 31 (1975) 255-260] quantile transform method and the Bulinski [Theory Probab. Appl. 40 (1995) 136-144] rate of convergence in the CLT.

http://arXiv.org/abs/math/0503661
http://front.math.ucdavis.edu/math.PR/0503661 (alternate)

3293. Moderate deviation principle for ergodic Markov chain. Lipschitz summands

Author(s): B. Delyon and A. Juditsky and R. Liptser

Abstract: For ${1/2}<\alpha<1$, we propose the MDP analysis for family $$ S^\alpha_n=\frac{1}{n^\alpha}\sum_{i=1}^nH(X_{i-1}), n\ge 1, $$ where $(X_n)_{n\ge 0}$ be a homogeneous ergodic Markov chain, $X_n\in \mathbb{R}^d$, when the spectrum of operator $P_x$ is continuous. The vector-valued function $H$ is not assumed to be bounded but the Lipschitz continuity of $H$ is required. The main helpful tools in our approach are Poisson's equation and Stochastic Exponential; the first enables to replace the original family by $\frac{1}{n^\alpha}M_n$ with a martingale $M_n$ while the second to avoid the direct Laplace transform analysis.

http://arXiv.org/abs/math/0503071
http://front.math.ucdavis.edu/math.PR/0503071 (alternate)

3294. Distances in random graphs with finite mean and infinite variance degrees

Author(s): Remco van der Hofstad and Gerard Hooghiemstra and Dmitri Znamenski

Abstract: In this paper we study random graphs with independent and identically distributed degrees of which the tail of the distribution function is regularly varying with exponent $\tau\in (2,3)$. The number of edges between two arbitrary nodes, also called the graph distance or hopcount, in a graph with $N$ nodes is investigated when $N\to \infty$. When $\tau\in (2,3)$, this graph distance grows like $2\frac{\log\log N}{|\log(\tau-2)|}$. In different papers, the cases $\tau>3$ and $\tau\in (1,2)$ have been studied. We also study the fluctuations around these asymptotic means, and describe their distributions. The results presented here improve upon results of Reittu and Norros, who prove an upper bound only.

http://arXiv.org/abs/math/0502581
http://front.math.ucdavis.edu/math.PR/0502581 (alternate)

3295. On tail distributions of supremum and quadratic variation of local martingales

Author(s): R. Liptser and A. Novikov

Abstract: We extend some known results relating the distribution tails of a continuous local martingale supremum and its quadratic variation to the case of locally square integrable martingales with bounded jumps. The predictable and optional quadratic variations are involved in the main result.

http://arXiv.org/abs/math/0503072
http://front.math.ucdavis.edu/math.PR/0503072 (alternate)

3296. Limit theorems for bipower variation in financial econometrics

Author(s): Ole E. Barndorff-Nielsen (DEPT Math Sci) and Svend E. Graversen (DEPT Math Sci), Jean Jacod (PMA), Neil Shephard (NUFFIELD College)

Abstract: In this paper we provide an asymptotic analysis of generalised bipower measures of the variation of price processes in financial economics. These measures encompass the usual quadratic variation, power variation and bipower variations which have been highlighted in recent years in financial econometrics. The analysis is carried out under some rather general Brownian semimartingale assumptions, which allow for standard leverage effects.

http://arXiv.org/abs/math/0503711
http://front.math.ucdavis.edu/math.PR/0503711 (alternate)

3297. Random walks in a Dirichlet environment

Author(s): Nathana\"el Enriquez and Christophe Sabot

Abstract: This paper states a law of large numbers for a random walk in a random iid environment on ${\mathbb Z}^d$, where the environment follows some Dirichlet distribution. Moreover, we give explicit bounds for the asymptotic velocity of the process and also an asymptotic expansion of this velocity at low disorder.

http://arXiv.org/abs/math/0503713
http://front.math.ucdavis.edu/math.PR/0503713 (alternate)

3298. Random walks in a random environment

Author(s): S R S Varadhan

Abstract: Random walks as well as diffusions in random media are considered. Methods are developed that allow one to establish large deviation results for both the `quenched' and the `averaged' case.

http://arXiv.org/abs/math/0503089
http://front.math.ucdavis.edu/math.PR/0503089 (alternate)

3299. Random Trees and General Branching Processes

Author(s): Anna Rudas and Balint Toth and Benedek Valko

Abstract: We consider a model of random tree growth, where at each time unit a new vertex is added and attached to an already existing vertex chosen at random. The probability with which a vertex with degree $k$ is chosen is proportional to $w(k)$, where the weight function $w$ is the parameter of the model. In the papers of B. Bollobas, O. Riordan, J. Spencer, G. Tusnady, and, independently, Mori, the asymptotic degree distribution is obtained for a model that is equivalent to the special case of ours, when the weight function is linear. The proof therein strongly relies on the linear choice of $w$. We give the asymptotical degree distribution for a wide range of weight functions. Moreover, we provide the asymptotic distribution of the tree itself as seen from a randomly selected vertex. The latter approach is new and gives full insight to the limiting structure of the tree. Our proof relies on the fact that considering the evolution of the random tree in continuous time, the process may be viewed as a general branching process, this way classical results can be applied.

http://arXiv.org/abs/math/0503728
http://front.math.ucdavis.edu/math.PR/0503728 (alternate)

3300. Mixed Poisson approximation of node depth distributions in random binary search trees

Author(s): Rudolf Grubel and Nikolce Stefanoski

Abstract: We investigate the distribution of the depth of a node containing a specific key or, equivalently, the number of steps needed to retrieve an item stored in a randomly grown binary search tree. Using a representation in terms of mixed and compounded standard distributions, we derive approximations by Poisson and mixed Poisson distributions; these lead to asymptotic normality results. We are particularly interested in the influence of the key value on the distribution of the node depth. Methodologically our message is that the explicit representation may provide additional insight if compared to the standard approach that is based on the recursive structure of the trees. Further, in order to exhibit the influence of the key on the distributional asymptotics, a suitable choice of distance of probability distributions is important. Our results are also applicable in connection with the number of recursions needed in Hoare's [Comm. ACM 4 (1961) 321-322] selection algorithm Find.

http://arXiv.org/abs/math/0503738
http://front.math.ucdavis.edu/math.PR/0503738 (alternate)

3301. On Fractional Tempered Stable Motion

Author(s): C. Houdr\'e and R. Kawai

Abstract: Fractional tempered stable motion (fTSm)} is defined and studied. FTSm has the same covariance structure as fractional Brownian motion, while having tails heavier than Gaussian but lighter than stable. Moreover, in short time it is close to fractional stable L\'evy motion, while it is approximately fractional Brownian motion in long time. A series representation of fTSm is derived and used for simulation and to study some of its sample path properties.

http://arXiv.org/abs/math/0503741
http://front.math.ucdavis.edu/math.PR/0503741 (alternate)

3302. On Layered Stable Processes

Author(s): C. Houdr\'e and R. Kawai

Abstract: Layered stable (multivariate) distributions and processes are defined and studied. A layered stable process combines stable trends of two different indices, one of them possibly Gaussian. More precisely, in short time, it is close to a stable process while, in long time, it approximates another stable (possibly Gaussian) process. We also investigate the absolute continuity of a layered stable process with respect to its short time limiting stable process. A series representation of layered stable processes is derived, giving insights into both the structure of the sample paths and of the short and long time behaviors. This series is further used for sample paths simulation.

http://arXiv.org/abs/math/0503742
http://front.math.ucdavis.edu/math.PR/0503742 (alternate)

3303. Measure free martingales

Author(s): Rajeeva L Karandikar and M G Nadkarni

Abstract: We give a necessary and sufficient condition on a sequence of functions on a set $\Omega$ under which there is a measure on $\Omega$ which renders the given sequence of functions a martingale. Further such a measure is unique if we impose a natural maximum entropy condition on the conditional probabilities.

http://arXiv.org/abs/math/0503099
http://front.math.ucdavis.edu/math.PR/0503099 (alternate)

3304. Metric stability for random walks (with applications in renormalization theory)

Author(s): Carlos G. Moreira (IMPA-Brazil) Daniel Smania (ICMC-USP-Brazil)

Abstract: Consider deterministic random walks F: I x Z -> I x Z, defined by F(x,n)=(f(x), K(x)+n), where f is an expanding Markov map on the interval I and K: I->Z. We study the universality (stability) of ergodic (for instance, recurrence and transience), geometric and multifractal properties in the class of perturbations of the type G(x,n)=(f_n(x), L(x,n)+n) which are topologically conjugate with F and f_n are expanding maps exponentially close to f when |n| goes to infinity. We give applications of these results in the study of the regularity of conjugacies between (generalized) infinitely renormalizable maps of the interval and the existence of wild attractors for one-dimensional maps.

http://arXiv.org/abs/math/0503736
http://front.math.ucdavis.edu/math.DS/0503736 (alternate)

3305. The Jammed Phase of the Biham-Middleton-Levine Traffic Model

Author(s): Omer Angel and Alexander E Holroyd and James B Martin

Abstract: Initially a car is placed with probability p at each site of the two-dimensional integer lattice. Each car is equally likely to be East-facing or North-facing, and different sites receive independent assignments. At odd time steps, each North-facing car moves one unit North if there is a vacant site for it to move into. At even time steps, East-facing cars move East in the same way. We prove that when p is sufficiently close to 1 traffic is jammed, in the sense that no car moves infinitely many times. The result extends to several variant settings, including a model with cars moving at random times, and higher dimensions.

http://arXiv.org/abs/math/0504001
http://front.math.ucdavis.edu/math.PR/0504001 (alternate)

3306. BSDE with quadratic growth and unbounded terminal value

Author(s): Philippe Briand (IRMAR) and Ying Hu (IRMAR)

Abstract: In this paper, we study the existence of solution to BSDE with quadratic growth and unbounded terminal value. We apply a localization procedure together with a priori bounds. As a byproduct, we apply the same method to extend a result on BSDEs with integrable terminal condition.

http://arXiv.org/abs/math/0504002
http://front.math.ucdavis.edu/math.PR/0504002 (alternate)

3307. The heat equation with multiplicative stable L\'evy noise

Author(s): Carl Mueller and Leonid Mytnik and Aurel Stan

Abstract: We study the heat equation with a random potential term. The potential is a one-sided stable noise, with positive jumps, which does not depend on time. To avoid singularities, we define the equation in terms of a construction similar to the Skorokhod integral or Wick product. We give a criterion for existence based on the dimension of the space variable, and the parameter p of the stable noise. Our arguments are different for p<1 and p>1.

http://arXiv.org/abs/math/0504027
http://front.math.ucdavis.edu/math.PR/0504027 (alternate)

3308. The Full Scaling Limit of Two-Dimensional Critical Percolation

Author(s): Federico Camia and Charles M. Newman

Abstract: We use SLE(6) paths to construct a process of continuum nonsimple loops in the plane and prove that this process coincides with the full continuum scaling limit of 2D critical site percolation on the triangular lattice -- that is, the scaling limit of the set of all interfaces between different clusters. Some properties of the loop process, including conformal invariance, are also proved. In the main body of the paper these results are proved while assuming, as argued by Schramm and Smirnov, that the percolation exploration path converges in distribution to the trace of chordal SLE(6). Then, in a lengthy appendix, a detailed proof is provided for this convergence to SLE(6), which itself relies on Smirnov's result that crossing probabilities converge to Cardy's formula.

http://arXiv.org/abs/math/0504036
http://front.math.ucdavis.edu/math.PR/0504036 (alternate)

3309. Minimax and adaptive estimation of the Wigner function in quantum homodyne tomography with noisy data

Author(s): Cristina Butucea (PMA and MODALX) and Madalin Guta and Luis Artiles

Abstract: We estimate the quantum state of a light beam from results of quantum homodyne measurements performed on identically prepared quantum systems. The state is represented through the Wigner function, a density on R2 which may take negative values but must respect intrinsic positivity constraints imposed by quantum physics. The effect of the losses due to detection inefficiencies which are always present in a real experiment is the addition to the tomographic data of independent Gaussian noise. We construct a kernel estimator for the Wigner function and prove that it is minimax efficient for the pointwise risk over a class of infinitely differentiable functions. For the L2 risk, we compute the upper bounds of a truncated kernel estimator over the same classes, restricted to functions with sub-Gaussian asymptotic behaviour. We construct adaptive estimators, i.e. which do not depend on the smoothness parameters, and prove that in some set-ups they attain the minimax rates for the corresponding smoothness class.

http://arXiv.org/abs/math/0504058
http://front.math.ucdavis.edu/math.PR/0504058 (alternate)

3310. Point process model of 1/f noise versus a sum of Lorentzians

Author(s): B. Kaulakys and V. Gontis and and M. Alaburda

Abstract: We present a simple point process model of $1/f^{\beta}$ noise, covering different values of the exponent $\beta$. The signal of the model consists of pulses or events. The interpulse, interevent, interarrival, recurrence or waiting times of the signal are described by the general Langevin equation with the multiplicative noise and stochastically diffuse in some interval resulting in the power-law distribution. Our model is free from the requirement of a wide distribution of relaxation times and from the power-law forms of the pulses. It contains only one relaxation rate and yields $1/f^ {\beta}$ spectra in a wide range of frequency. We obtain explicit expressions for the power spectra and present numerical illustrations of the model. Further we analyze the relation of the point process model of $1/f$ noise with the Bernamont-Surdin-McWhorter model, representing the signals as a sum of the uncorrelated components. We show that the point process model is complementary to the model based on the sum of signals with a wide-range distribution of the relaxation times. In contrast to the Gaussian distribution of the signal intensity of the sum of the uncorrelated components, the point process exhibits asymptotically a power-law distribution of the signal intensity. The developed multiplicative point process model of $1/f^{\beta}$ noise may be used for modeling and analysis of stochastic processes in different systems with the power-law distribution of the intensity of pulsing signals.

http://arXiv.org/abs/cond-mat/0504025
http://front.math.ucdavis.edu/cond-mat/0504025 (alternate)

3311. A random walk proof of the Erdos-Taylor conjecture

Author(s): Jay Rosen

Abstract: For the simple random walk in Z^2 we study those points which are visited an unusually large number of times, and provide a new proof of the Erdos-Taylor conjecture describing the number of visits to the most visited point.

http://arXiv.org/abs/math/0503108
http://front.math.ucdavis.edu/math.PR/0503108 (alternate)

3312. What is always stable in nonlinear filtering?

Author(s): P. Chigansky and R. Liptser

Abstract: This note addresses certain stability properties of the nonlinear filtering equation in discrete time. The available positive and negative results indicate that much depends on the structure of the signal state space, its ergodic properties and observations regularity. We show that certain predicting estimates are stable under surprisingly general assumptions.

http://arXiv.org/abs/math/0504094
http://front.math.ucdavis.edu/math.PR/0504094 (alternate)

3313. How likely is an i.i.d. degree sequence to be graphical?

Author(s): Richard Arratia and Thomas M. Liggett

Abstract: Given i.i.d. positive integer valued random variables D_1,...,D_n, one can ask whether there is a simple graph on n vertices so that the degrees of the vertices are D_1,...,D_n. We give sufficient conditions on the distribution of D_i for the probability that this be the case to be asymptotically 0, {1/2} or strictly between 0 and {1/2}. These conditions roughly correspond to whether the limit of nP(D_i\geq n) is infinite, zero or strictly positive and finite. This paper is motivated by the problem of modeling large communications networks by random graphs.

http://arXiv.org/abs/math/0504096
http://front.math.ucdavis.edu/math.PR/0504096 (alternate)

3314. The universality classes in the parabolic Anderson model

Author(s): Remco van der Hofstad and Wolfgang Koenig and Peter Moerters

Abstract: We discuss the long time behaviour of the parabolic Anderson model, the Cauchy problem for the heat equation with random potential on $\Z^d$. We consider general i.i.d. potentials and show that exactly \emph{four} qualitatively different types of intermittent behaviour can occur. These four universality classes depend on the upper tail of the potential distribution: (1) tails at $\infty$ that are thicker than the double-exponential tails, (2) double-exponential tails at $\infty$ studied by G\"artner and Molchanov, (3) a new class called \emph{almost bounded potentials}, and (4) potentials bounded from above studied by Biskup and K\"onig. The new class (3), which contains both unbounded and bounded potentials, is studied in both the annealed and the quenched setting. We show that intermittency occurs on unboundedly increasing islands whose diameter is slowly varying in time. The characteristic variational formulas describing the optimal profiles of the potential and of the solution are solved explicitly by parabolas, respectively, Gaussian densities.

http://arXiv.org/abs/math/0504102
http://front.math.ucdavis.edu/math.PR/0504102 (alternate)

3315. Invariance principles for labeled mobiles and bipartite planar maps

Author(s): Jean-Fran\c{c}ois Marckert (LM-Versailles) and Gr\'{e}gory Miermont (LM-Orsay)

Abstract: A class of labeled trees, called mobiles, was introduced by Bouttier-di Francesco and Guitter in order to generalize the bijective studies of planar maps initiated by Cori-Vauquelin and Schaeffer. We prove an invariance principle for rescaled random mobiles associated with bipartite random planar maps under a Boltzmann distribution. We infer that the latter converge in a certain sense to the Brownian map introduced by Marckert and Mokkadem, which encompasses results of Chassaing and Schaeffer on quadrangulations (although in a slightly different context). These results are derived from a new invariance principle for a class of two-type Galton-Watson trees coupled with a spatial motion, which are shown to converge to the Brownian snake.

http://arXiv.org/abs/math/0504110
http://front.math.ucdavis.edu/math.PR/0504110 (alternate)

3316. Tracy-Widom limit for the largest eigenvalue of a large class of complex Wishart matrices

Author(s): Noureddine El Karoui

Abstract: We study the limiting behavior of the largest eigenvalue of a large class of complex Wishart matrices. In other words, let X be an n*p matrix, and let its rows be i.i.d complex normal N_{C}(0,Sigma_p). We denote by H_p the spectral distribution of Sigma_p, and call lambda_i's its ordered eigenvalues. Let us call l_i's the ordered eigenvalues of X^*X and c the unique root in [0,1/lambda_1(Sigma_p)) of the equation \int ((lambda c)/(1-\lambda c))^2 dH_p(lambda) = n/p. The main result of this paper is that, under technical conditions on (Sigma_p,n,p), we have, when n->\infty, (l_1(X^*X)-n mu)/(n^{1/3} sigma) -> TW_2 . We give explicit formulas for mu and sigma, that depend non trivially on c. Here TW_2 denotes the Tracy-Widom law appearing in the study of the Gaussian Unitary Ensemble. This theorem applies to a number of covariance models found in applications, including well-behaved Toeplitz matrices and covariance matrices whose spectral distribution is a sum of atoms (under some conditions on the mass of the atoms). Generalizations of the theorem to certain spiked versions of models in G and a.s statements about l_1/n are given. Most known examples of convergence of the largest eigenvalue of a complex sample covariance matrix to this Tracy-Widom law are subcases of this result.

http://arXiv.org/abs/math/0503109
http://front.math.ucdavis.edu/math.PR/0503109 (alternate)

3317. Determinantal Processes and Independence

Author(s): J. Ben Hough and Manjunath Krishnapur and Yuval Peres and Balint Virag

Abstract: We give a probabilistic introduction to determinantal and permanental point processes. Determinantal processes arise in physics (fermions, eigenvalues of random matrices) and in combinatorics (nonintersecting paths, random spanning trees). They have the striking property that the number of points in a region $D$ is a sum of independent Bernoulli random variables, with parameters which are eigenvalues of the relevant operator on $L^2(D)$. Moreover, any determinantal process can be represented as a mixture of determinantal projection processes. We give a simple explanation for these known facts, and establish analogous representations for permanental processes, with geometric variables replacing the Bernoulli variables. These representations lead to simple proofs of existence criteria and central limit theorems, and unify known results on the distribution of absolute values in certain processes with radially symmetric distributions.

http://arXiv.org/abs/math/0503110
http://front.math.ucdavis.edu/math.PR/0503110 (alternate)

3318. Random walk on the incipient infinite cluster on trees

Author(s): Martin T. Barlow and Takashi Kumagai

Abstract: Let ${\cal G}$ be the incipient infinite cluster (IIC) for percolation on a homogeneous tree of degree $n_0+1$. We obtain estimates for the transition density of the continuous time simple random walk $Y$ on ${\cal G}$; the process satisfies anomalous diffusion and has spectral dimension 4/3.

http://arXiv.org/abs/math/0503118
http://front.math.ucdavis.edu/math.PR/0503118 (alternate)

3319. Quantitative concentration inequalities for empirical measures on non-compact spaces

Author(s): Francois Bolley and Arnaud Guillin and Cedric Villani

Abstract: We establish some quantitative concentration estimates for the empirical measure of many independent variables, in transportation distances. As an application, we provide some error bounds for particle simulations in a model mean field problem. The tools include coupling arguments, as well as regularity and moments estimates for solutions of certain diffusive partial differential equations.

http://arXiv.org/abs/math/0503123
http://front.math.ucdavis.edu/math.PR/0503123 (alternate)

3320. On the Bias of Traceroute Sampling; or, Power-law Degree Distributions in Regular Graphs

Author(s): Dimitris Achlioptas and Aaron Clauset and David Kempe and and Cristopher Moore

Abstract: Understanding the structure of the Internet graph is a crucial step for building accurate network models and designing efficient algorithms for Internet applications. Yet, obtaining its graph structure is a surprisingly difficult task, as edges cannot be explicitly queried. Instead, empirical studies rely on traceroutes to build what are essentially single-source, all-destinations, shortest-path trees. These trees only sample a fraction of the network's edges, and a recent paper by Lakhina et al. found empirically that the resuting sample is intrinsically biased. For instance, the observed degree distribution under traceroute sampling exhibits a power law even when the underlying degree distribution is Poisson. In this paper, we study the bias of traceroute sampling systematically, and, for a very general class of underlying degree distributions, calculate the likely observed distributions explicitly. To do this, we use a continuous-time realization of the process of exposing the BFS tree of a random graph with a given degree distribution, calculate the expected degree distribution of the tree, and show that it is sharply concentrated. As example applications of our machinery, we show how traceroute sampling finds power-law degree distributions in both delta-regular and Poisson-distributed random graphs. Thus, our work puts the observations of Lakhina et al. on a rigorous footing, and extends them to nearly arbitrary degree distributions.

http://arXiv.org/abs/cond-mat/0503087
http://front.math.ucdavis.edu/cond-mat/0503087 (alternate)

3321. The critical Ising model on trees, concave recursions and nonlinear capacity

Author(s): Robin Pemantle and Yuval Peres

Abstract: We consider the Ising model on a general tree under various boundary conditions: all plus, free and spin-glass. In each case, we determine when the root is influenced by the boundary values in the limit as the boundary recedes to infinity. We obtain exact capacity criteria that govern behavior at critical temperatures. For plus boundary conditions, an $L^3$ capacity arises. In particular, on a spherically symmetric tree that has $n^c b^n$ vertices at level $n$ (up to bounded factors), we prove that there is a unique Gibbs measure for the ferromagnetic Ising model if and only if $c$ is at most 1/2. Our proofs are based on a new link between nonlinear recursions on trees and $L^p$ capacities.

http://arXiv.org/abs/math/0503137
http://front.math.ucdavis.edu/math.PR/0503137 (alternate)

3322. How large a disc is covered by a random walk in $n$ steps?

Author(s): Amir Dembo and Yuval Peres and Jay Rosen

Abstract: We show that the largest disc covered by a simple random walk on the planar square lattice after $n$ steps has radius $n^{1/4+o(1)}$, thus resolving an open problem of P. R\'ev\'esz (1990). We also show that almost surely, for infinitely many values of $n$ it takes about $n^{1/2+o(1)}$ steps after step $n$ for the random walk to reach the first previously unvisited site (and the exponent 1/2 is sharp). This resolves a problem raised by P. R\'ev\'esz (1993). Additional results on multiple covering are obtained as well.

http://arXiv.org/abs/math/0503139
http://front.math.ucdavis.edu/math.PR/0503139 (alternate)

3323. Infinite dimensional stochastic differential equations of Ornstein-Uhlenbeck type

Author(s): Siva R. Athreya and Richard F. Bass and Maria Gordina and Edwin A. Perkins

Abstract: We consider the operator $$\sL f(x)=\tfrac12 \sum_{i,j=1}^\infty a_{ij}(x)\frac{\del^2 f}{\del x_i \del x_j}(x)-\sum_{i=1}^\infty \lam_i x_i b_i(x) \frac{\del f}{\del x_i}(x).$$ We prove existence and uniqueness of solutions to the martingale problem for this operator under appropriate conditions on the $a_{ij}, b_i$, and $\lam_i$. The process corresponding to $\sL$ solves an infinite dimensional stochastic differential equation similar to that for the infinite dimensional Ornstein-Uhlenbeck process.

http://arXiv.org/abs/math/0503165
http://front.math.ucdavis.edu/math.PR/0503165 (alternate)

3324. On Chordal and Bilateral SLE in multiply connected domains

Author(s): Robert O. Bauer and Roland M. Friedrich

Abstract: We discuss the possible candidates for conformally invariant random non-self-crossing curves which begin and end on the boundary of a multiply connected planar domain, and which satisfy a Markovian-type property. We consider both, the case when the curve connects a boundary component to itself (chordal), and the case when the curve connects two different boundary components (bilateral). We establish appropriate extensions of Loewner's equation to multiply connected domains for the two cases. We show that a curve in the domain induces a motion on the boundary and that this motion is enough to first recover the motion of the moduli of the domain and then, second, the curve in the interior. For random curves in the interior we show that the induced random motion on the boundary is not Markov if the domain is multiply connected, but that the random motion on the boundary together with the random motion of the moduli forms a Markov process. In the chordal case, we show that this Markov process satisfies Brownian scaling and discuss how this limits the possible conformally invariant random non-self-crossing curves. We show that the possible candidates are labeled by a real constant and a function homogeneous of degree minus one which describes the interaction of the random curve with the boundary. We show that the random curve has the locality property if the interaction term vanishes and the real parameter equals six.

http://arXiv.org/abs/math/0503178
http://front.math.ucdavis.edu/math.PR/0503178 (alternate)

3325. From N-parameter fractional Brownian motions to N-parameter multifractional Brownian motions

Author(s): E. Herbin

Abstract: Multifractional Brownian motion is an extension of the well-known fractional Brownian motion where the Holder regularity is allowed to vary along the paths. In this paper, two kind of multi-parameter extensions of mBm are studied: one is isotropic while the other is not. For each of these processes, a moving average representation, a harmonizable representation, and the covariance structure are given. The Holder regularity is then studied. In particular, the case of an irregular exponent function H is investigated. In this situation, the almost sure pointwise and local Holder exponents of the multi-parameter mBm are proved to be equal to the correspondent exponents of H. Eventually, a local asymptotic self-similarity property is proved. The limit process can be another process than fBm.

http://arXiv.org/abs/math/0503182
http://front.math.ucdavis.edu/math.PR/0503182 (alternate)

3326. Examples of Groups that are Measure Equivalent to the Free Group

Author(s): Damien Gaboriau (UMPA-ENSL)

Abstract: Measure Equivalence (ME) is the measure theoretic counterpart of quasi-isometry. This field grew considerably during the last years, developing tools to distinguish between different ME classes of countable groups. On the other hand, contructions of ME equivalent groups are very rare. We present a new method, based on a notion of measurable free-factor, and we apply it to exhibit a new family of groups that are measure equivalent to the free group. We also present a quite extensive survey on results about Measure Equivalence for countable groups.

http://arXiv.org/abs/math/0503181
http://front.math.ucdavis.edu/math.DS/0503181 (alternate)

3327. Orthogonal Polynomials and Fluctuations of Random Matrices

Author(s): Timothy Kusalik and James A. Mingo and and Roland Speicher

Abstract: In this paper we establish a connection between the fluctuations of Wishart random matrices, shifted Chebyshev polynomials, and planar diagrams whose linear span form a basis for the irreducible representations of the annular Temperly-Lieb algebra.

http://arXiv.org/abs/math/0503169
http://front.math.ucdavis.edu/math.OA/0503169 (alternate)

3328. Counting Connected Graphs Asymptotically

Author(s): Remco van der Hofstad and Joel Spencer

Abstract: We find the asymptotic number of connected graphs with $k$ vertices and $k-1+l$ edges when $k,l$ approach infinity, reproving a result of Bender, Canfield and McKay. We use the {\em probabilistic method}, analyzing breadth-first search on the random graph $G(k,p)$ for an appropriate edge probability $p$. Central is analysis of a random walk with fixed beginning and end which is tilted to the left.

http://arXiv.org/abs/math/0502579
http://front.math.ucdavis.edu/math.CO/0502579 (alternate)

3329. On q-functional equations and excursion moments

Author(s): Christoph Richard

Abstract: We analyse q-functional equations arising from tree-like combinatorial structures, which are counted by size, internal path length and certain generalisations thereof. The corresponding counting parameters are labelled by an integer k>1. We show the existence of a joint limit distribution for these parameters in the limit of infinite size, if the size generating function has a square root as dominant singularity. The limit distribution coincides with that of integrals of (k-1)th powers of the standard Brownian excursion. Our method yields a recursion for the moments of the joint distribution and admits an extension to other types of singularities.

http://arXiv.org/abs/math/0503198
http://front.math.ucdavis.edu/math.CO/0503198 (alternate)

3330. A set-indexed fractional Brownian motion

Author(s): E. Herbin and E. Merzbach

Abstract: We define and prove the existence of a fractional Brownian motion indexed by a collection of closed subsets of a measure space. This process is a generalization of the set-indexed Brownian motion, when the condition of independance is relaxed. Relations with the Levy fractional Brownian motion and with the fractional Brownian sheet are studied. We prove stationarity of the increments and a property of self-similarity with respect to the action of solid motions. Regularity conditions are exhibited. Finally, behavior of the set-indexed fractional Brownian motion along increasing paths is analysed.

http://arXiv.org/abs/math/0503211
http://front.math.ucdavis.edu/math.PR/0503211 (alternate)

3331. Entropy-driven phase transition in a polydisperse hard-rods lattice system

Author(s): Dmitry Ioffe and Yvan Velenik (LMRS) and Milos Zahradnik

Abstract: We study a system of rods on the 2d square lattice, with hard-core exclusion. Each rod has a length between 2 and N. We show that, when N is sufficiently large, and for suitable fugacity, there are several distinct Gibbs states, with orientational long-range order. This is in sharp contrast with the case N=2 (the monomer-dimer model), for which Heilmann and Lieb proved absence of phase transition at any fugacity. This is the first example of a pure hard-core system with phases displaying orientational order, but not translational order; this is a fundamental characteristic feature of liquid crystals.

http://arXiv.org/abs/math/0503222
http://front.math.ucdavis.edu/math.PR/0503222 (alternate)

3332. An Inductive Proof of the Berry-Esseen Theorem for Character Ratios

Author(s): Jason Fulman

Abstract: Bolthausen used a variation of Stein's method to give an inductive proof of the Berry-Esseen theorem for sums of independent, identically distributed random variables. We modify this technique to prove a Berry-Esseen theorem for character ratios of a random representation of the symmetric group on transpositions. An analogous result is proved for Jack measure on partitions.

http://arXiv.org/abs/math/0503227
http://front.math.ucdavis.edu/math.CO/0503227 (alternate)

3333. Max-Semi-Selfdecomposable Laws and Related Processes

Author(s): S Satheesh and E Sandhya

Abstract: Methods of construction of Max-semi-selfdecompsable laws are given. Implications of this method in random time changed extremal processes are discussed. Max-autoregressive model is introduced and characterized using the max-semi-selfdecompsable laws and exponential max-semi-stable laws. Some comments regarding the infinite divisibility of semi-stable and max-semi-stable laws are given.

http://arXiv.org/abs/math/0503232
http://front.math.ucdavis.edu/math.PR/0503232 (alternate)

3334. Discrete interpolation between monotone probability and free probability

Author(s): Romuald Lenczewski and Rafal Salapata

Abstract: We construct a sequence of states called m-monotone product states which give a discrete interpolation between the monotone product of states of Muraki and the free product of states of Avitzour and Voiculescu in free probability. We derive the associated basic limit theorems and develop the combinatorics based on non-crossing ordered partitions with monotone order starting from depth m. The Hilbert space representations of the limit mixed moments in the invariance principle lead to m-monotone Gaussian operators living in m-monotone Fock spaces, which are truncations of the free Fock space over the square-integrable functions on the non-negative real line (m=1 gives the monotone Fock space). A new type of combinatorics of inner blocks leads to explicit formulas for the mixed moments of m-monotone Gaussian operators, which are new even in the case of monotone independent Gaussian operators with arcsine distributions.

http://arXiv.org/abs/math/0502570
http://front.math.ucdavis.edu/math.QA/0502570 (alternate)

3335. Riffle shuffles of decks with repeated cards

Author(s): Mark Conger and D. Viswanath

Abstract: By a well-known result of Bayer and Diaconis, the maximum entropy model of the common riffle shuffle implies that the number of riffle shuffles necessary to mix a standard deck of 52 cards is either 7 or 11 -- with the former number applying when the metric used to define mixing is the total variation distance and the later when it is the separation distance. This and other related results assume all 52 cards in the deck to be distinct and require all $52!$ permutations of the deck to be almost equally likely for the deck to be considered well mixed. In many instances, not all cards in the deck are distinct and only the sets of cards dealt out to players, and not the order in which they are dealt out to each player, needs to be random. We derive transition probabilities under riffle shuffles between decks with repeated cards to cover some instances of the type just described. We focus on decks with cards all of which are labeled either 1 or 2 and describe the consequences of having a symmetric starting deck of the form $1,...,1,2...,2$ or $1,2,..., 1,2$. Finally, we consider mixing times for common card games.

http://arXiv.org/abs/math/0503233
http://front.math.ucdavis.edu/math.PR/0503233 (alternate)

3336. Bermudan option pricing based on piecewise harmonic interpolation and the r\'eduite

Author(s): Frederik S. Herzberg

Abstract: We consider an iterative Bermudan option pricing algorithm based on piecewise harmonic interpolation and give an explicit constructive characterisation of the smallest fixed point of the iteration step as the approximate price of the perpetual Bermudan option. The same arguments work for a related iterative algorithm based on the approximation of subharmonic functions via the r\'eduite associated with a given closed $F_{\sigma}$ subset of $\RR^d$.

http://arXiv.org/abs/math/0503234
http://front.math.ucdavis.edu/math.PR/0503234 (alternate)

3337. A brief note on the soundness of Bermudan option pricing via cubature

Author(s): Frederik S. Herzberg

Abstract: The subject of this study is an iterative Bermudan option pricing algorithm based on (high-dimensional) cubature. We show that the sequence of Bermudan prices (as functions of the underlying assets' logarithmic start prices) resulting from the iteration is bounded and increases monotonely to the approximate perpetual Bermudan option price; the convergence is linear in the supremum norm with the discount factor being the convergence factor. Furthermore, we prove a characterisation of this approximated perpetual Bermudan price as the smallest fixed point of the iteration procedure.

http://arXiv.org/abs/math/0503235
http://front.math.ucdavis.edu/math.PR/0503235 (alternate)

3338. Spherical Asymptotics for the Rotor-Router Model in Z^d

Author(s): Lionel Levine and Yuval Peres

Abstract: The rotor-router model is a deterministic analogue of random walk invented by Jim Propp. It can be used to define a deterministic aggregation model analogous to internal diffusion limited aggregation. We prove an isoperimetric inequality for the exit time of simple random walk from a finite region in Z^d, and use this to prove that the shape of the rotor-router aggregation model in Z^d, suitably rescaled, converges to a Euclidean ball in R^d.

http://arXiv.org/abs/math/0503251
http://front.math.ucdavis.edu/math.PR/0503251 (alternate)

3339. Some explicit Krein representations of certain subordinators, including the Gamma process

Author(s): Catherine Donati-Martin (PMA) and Marc Yor (PMA)

Abstract: We give a representation of the Gamma subordinator as a Krein functional of Brownian motion, using the known representations for stable subordinators and Esscher transforms. In particular, we have obtained Krein representations of the subordinators which govern the two parameter Poisson-Dirichlet family of distributions.

http://arXiv.org/abs/math/0503254
http://front.math.ucdavis.edu/math.PR/0503254 (alternate)

3340. An invariance principle for conditioned trees

Author(s): Jean-Francois Le Gall (DMA-ENS Paris)

Abstract: We consider Galton-Watson trees associated with a critical offspring distribution and conditioned to have exactly $n$ vertices. These trees are embedded in the real line by affecting spatial positions to the vertices, in such a way that the increments of the spatial positions along edges of the tree are independent variables distributed according to a symmetric probability distribution on the real line. We then condition on the event that all spatial positions are nonnegative. Under suitable assumptions on the offspring distribution and the spatial displacements, we prove that these conditioned spatial trees converge as $n\to\infty$, modulo an appropriate rescaling, towards the conditioned Brownian tree that was studied in previous work. Applications are given to asymptotics for random quadrangulations.

http://arXiv.org/abs/math/0503263
http://front.math.ucdavis.edu/math.PR/0503263 (alternate)

3341. On Generalized Computable Universal Priors and their Convergence

Author(s): Marcus Hutter

Abstract: Solomonoff unified Occam's razor and Epicurus' principle of multiple explanations to one elegant, formal, universal theory of inductive inference, which initiated the field of algorithmic information theory. His central result is that the posterior of the universal semimeasure M converges rapidly to the true sequence generating posterior mu, if the latter is computable. Hence, M is eligible as a universal predictor in case of unknown mu. The first part of the paper investigates the existence and convergence of computable universal (semi)measures for a hierarchy of computability classes: recursive, estimable, enumerable, and approximable. For instance, M is known to be enumerable, but not estimable, and to dominate all enumerable semimeasures. We present proofs for discrete and continuous semimeasures. The second part investigates more closely the types of convergence, possibly implied by universality: in difference and in ratio, with probability 1, in mean sum, and for Martin-Loef random sequences. We introduce a generalized concept of randomness for individual sequences and use it to exhibit difficulties regarding these issues. In particular, we show that convergence fails (holds) on generalized-random sequences in gappy (dense) Bernoulli classes.

http://arXiv.org/abs/cs/0503026
http://front.math.ucdavis.edu/cs.LG/0503026 (alternate)

3342. The Stable Manifold Theorem for Semilinear Stochastic Evolution Equations and Stochastic Partial Differential Equations I: The Stochastic Semiflow

Author(s): Salah-Eldin A Mohammed and Tusheng Zhang and Huaizhong Zhao

Abstract: The main objective of this work is to characterize the pathwise local structure of solutions of semilinear stochastic evolution equations (see's) and stochastic partial differential equations (spde's) near stationary solutions. Such characterization is realized through the long-term behavior of the solution field near stationary points. The analysis falls in two parts I, II. In Part I (this paper), we prove a general existence and compactness theorem for $C^k$-cocycles of semilinear see's and spde's. Our results cover a large class of semilinear see's as well as certain semilinear spde's with non-Lipschitz terms such as stochastic reaction diffusion equations and the stochastic Burgers equation with additive infinite-dimensional noise. In Part II of this work ([M-Z-Z]), we establish a local stable manifold theorem for non-linear see's and spde's.

http://arXiv.org/abs/math/0503320
http://front.math.ucdavis.edu/math.PR/0503320 (alternate)

3343. The Stable Manifold Theorem for Semilinear Stochastic Evolution Equations and Stochastic Partial Differential Equations II: Existence of stable and unstable manifolds

Author(s): Salah-Eldin A. Mohammed and Tusheng Zhang and Huaizhong Zhao

Abstract: This article is a sequel to [M.Z.Z.1] aimed at completing the characterization of the pathwise local structure of solutions of semilinear stochastic evolution equations (see's) and stochastic partial differential equations (spde's) near stationary solutions. Stationary solution are viewed as random points in the infinite-dimensional state space, and the characterization is expressed in terms of the almost sure long-time behavior of trajectories of the equation in relation to the stationary solution. More specifically, we establish local stable manifold theorems for semilinear see's and spde's (Theorems 4.1-4.4). These results give smooth stable and unstable manifolds in the neighborhood of a hyperbolic stationary solution of the underlying stochastic equation. The stable and unstable manifolds are stationary, live in a stationary tubular neighborhood of the stationary solution and are asymptotically invariant under the stochastic semiflow of the see/spde. The proof uses infinite-dimensional multiplicative ergodic theory techniques and interpolation arguments (Theorem 2.1).

http://arXiv.org/abs/math/0503321
http://front.math.ucdavis.edu/math.PR/0503321 (alternate)

3344. Boundary Harnack Principle for fractional powers of Laplacian on the Sierpinski carpet

Author(s): Andrzej Stos (LMP-Clermont)

Abstract: We prove the Boundary Harnack Principle related to fractional powers of Laplacian for some natural regions in the two-dimensional Sierpinski carpet. This is a natual application of a probabilistic method based on the Ikeda-Watanabe formula

http://arXiv.org/abs/math/0503333
http://front.math.ucdavis.edu/math.PR/0503333 (alternate)

3345. A note on exact likelihoods of the Carr-Wu models for leverage effects and volatility in financial economics

Author(s): Lancelot F. James

Abstract: Recently Carr and Wu (2004, 2005) and also Huang and Wu (2004) show that most stochastic processes used in traditional option pricing models can be cast as special cases of time-changed L\'evy processes. In particular these are models which can be tailored to exhibit correlated jumps in both the log price of assets and the instantaneous volatility. Naturally similar to a recent work of Barndorff-Nielsen and Shephard (2001a, b), such models may be used in a likelihood based framework. These likelihoods are based on the unobserved integrated volatility, rather than the instantaneous volatility. James (2005) establishes general results for the likelihood and estimation of a large class of such models which include possible leverage effects. In this note we show that exact expressions for likelihood models based on generalizations of Carr and Wu (2005) and Huang and Wu (2005), follow essentially from the arguments in Theorem 5.1 in James (2005) with some slight modification. This serves to formally verify a claim made by James (2005).

http://arXiv.org/abs/math/0503314
http://front.math.ucdavis.edu/math.ST/0503314 (alternate)

3346. Poisson kernels of half-spaces in real hyperbolic spaces

Author(s): T. Byczkowski and P. Graczyk and A. Stos

Abstract: We provide an integral formula for the Poisson kernel of half-spaces for Brownian motion in real hyperbolic space $\H^n$. This enables us to find asymptotic properties of the kernel. Our starting point is the formula for its Fourier transform. When $n=3$, 4 or 6 we give an explicit formula for the Poisson kernel itself. In the general case we give various asymptotics and show convergence to the Poisson kernel of $\H^n$.

http://arXiv.org/abs/math/0503372
http://front.math.ucdavis.edu/math.PR/0503372 (alternate)

3347. Doob's maximal identity, multiplicative decompositions and enlargements of filtrations

Author(s): A. Nikeghbali and M. Yor

Abstract: In the theory of progressive enlargements of filtrations, the supermartingale $Z_{t}=\mathbf{P}(g>t\mid \mathcal{F}_{t}) $ associated with an honest time $g$, and its additive (Doob-Meyer) decomposition, play an essential role. In this paper, we propose an alternative approach, using a multiplicative representation for the supermartingale $Z_{t}$, based on Doob's maximal identity. We thus give new examples of progressive enlargements. Moreover, we give, in our setting, a proof of the decomposition formula for martingales, using initial enlargement techniques, and use it to obtain some path decompositions given the maximum or minimum of some processes.

http://arXiv.org/abs/math/0503386
http://front.math.ucdavis.edu/math.PR/0503386 (alternate)

3348. An annihilating-branching particle model for the heat equation with average temperature zero

Author(s): Krzysztof Burdzy and Jeremy Quastel

Abstract: We consider two species of particles performing random walks in a domain in Euclidean space with reflecting boundary conditions, which annihilate on contact. In addition there is a conservation law so that the total number of particles of each type is preserved: When the two particles of different species annihilate each other, particles of each species, chosen at random, give birth. We assume initially equal numbers of each species and show that the system has a diffusive scaling limit in which the densities of the two species are well approximated by the positive and negative parts of the solution of the heat equation normalized to have constant $L^1$ norm. In particular, the higher Neumann eigenfunctions appear as asymptotically stable states at the diffusive time scale.

http://arXiv.org/abs/math/0503395
http://front.math.ucdavis.edu/math.PR/0503395 (alternate)

3349. The reversible nearest particle systgems on a finite interval

Author(s): Dayue Chen and Juxin Liu and Fuxi Zhang

Abstract: In this paper we study a one-parameter family of attractive reversible nearest particle system on a finite interval. As the length of the interval increases, the time that the nearest particle system first hits the empty set increases in different order, from logarithmic to exponential, according to the intensity of interaction. In particular, at the critical case, the first hitting time increases in a polynomial order.

http://arXiv.org/abs/math/0503409
http://front.math.ucdavis.edu/math.PR/0503409 (alternate)

3350. Inside singularity sets of random Gibbs measures

Author(s): Julien Barral and Stephane Seuret

Abstract: We evaluate the scale at which the multifractal structure of some random Gibbs measures becomes discernible. The value of this scale is obtained through what we call the growth speed in H\"older singularity sets of a Borel measure. This growth speed yields new information on the multifractal behavior of the rescaled copies involved in the structure of statistically self-similar Gibbs measures. Our results are useful to understand the multifractal nature of various heterogeneous jump processes.

http://arXiv.org/abs/math/0503420
http://front.math.ucdavis.edu/math.PR/0503420 (alternate)

3351. Renewal of singularity sets of statistically self-similar measures

Author(s): Julien Barral and Stephane Seuret

Abstract: This paper investigates new properties concerning the multifractal structure of a class of statistically self-similar measures. These measures include the well-known Mandelbrot multiplicative cascades, sometimes called independent random cascades. We evaluate the scale at which the multifractal structure of these measures becomes discernible. The value of this scale is obtained through what we call the growth speed in H\"older singularity sets of a Borel measure. This growth speed yields new information on the multifractal behavior of the rescaled copies involved in the structure of statistically self-similar measures. Our results are useful to understand the multifractal nature of various heterogeneous jump processes.

http://arXiv.org/abs/math/0503421
http://front.math.ucdavis.edu/math.PR/0503421 (alternate)

3352. A polyhedral Markov field - pushing the Arak-Surgailis construction into three dimensions

Author(s): Tomasz Schreiber

Abstract: The purpose of the paper is to construct a polyhedral Markov field in ${\mathbb R}^3$ in analogy with the planar construction of the original Arak (1982) polygonal Markov field. We provide a dynamic construction of the process in terms of evolution of two-dimensional multi-edge systems tracing polyhedral boundaries of the field in three-dimensional time-space. We also give a general algorithm for simulating Gibbsian modifications of the constructed polyhedral field.

http://arXiv.org/abs/math/0503429
http://front.math.ucdavis.edu/math.PR/0503429 (alternate)

3353. Baysian inference via classes of normalized random measures

Author(s): Lancelot F. James and Antonio Lijoi and Igor Pruenster

Abstract: One of the main research areas in Bayesian Nonparametrics is the proposal and study of priors which generalize the Dirichlet process. Here we exploit theoretical properties of Poisson random measures in order to provide a comprehensive Bayesian analysis of random probabilities which are obtained by an appropriate normalization. Specifically we achieve explicit and tractable forms of the posterior and the marginal distributions, including an explicit and easily used description of generalizations of the important Blackwell-MacQueen P\'olya urn distribution. Such simplifications are achieved by the use of a latent variable which admits quite interesting interpretations which allow to gain a better understanding of the behaviour of these random probability measures. It is noteworthy that these models are generalizations of models considered by Kingman (1975) in a non-Bayesian context. Such models are known to play a significant role in a variety of applications including genetics, physics, and work involving random mappings and assemblies. Hence our analysis is of utility in those contexts as well. We also show how our results may be applied to Bayesian mixture models and describe computational schemes which are generalizations of known efficient methods for the case of the Dirichlet process. We illustrate new examples of processes which can play the role of priors for Bayesian nonparametric inference and finally point out some interesting connections with the theory of generalized gamma convolutions initiated by Thorin and further developed by Bondesson.

http://arXiv.org/abs/math/0503394
http://front.math.ucdavis.edu/math.ST/0503394 (alternate)

3354. A stochastic approximation algorithm with multiplicative step size adaptation

Author(s): Alexander Plakhov and Pedro Cruz

Abstract: An algorithm of searching a zero of an unknown undimensional function is considered, measured at a point x with some error. The step sizes are random positive values and are calculated according to the rule: if two consecutive iterations are in same direction step is multiplied by u>1, otherwise, it is multiplied by 01, divergence. Due to the multiplicative rule of updating of the step, it is natural to expect that the sequence converges rapidly: like a geometric progression (if convergence takes place), but the limit value may not coincide with, but instead, approximates one of zeros of the function. By adjusting the parameters u and d, one can reach necessary precision of approximation; higher precision is obtained at the expense of lower convergence rate.

http://arXiv.org/abs/math/0503434
http://front.math.ucdavis.edu/math.ST/0503434 (alternate)

3355. On approximate pattern matching for a class of Gibbs random fields

Author(s): J.R. Chazottes and F. Redig and E. Verbitskiy

Abstract: We prove an exponential approximation for the law of approximate occurrence of typical patterns for a class of Gibbsian sources on the lattice $\mathbb Z^d$, $d\ge 2$. From this result, we deduce a law of large numbers and a large deviation result for the the waiting time of distorted patterns.

http://arXiv.org/abs/math/0503008
http://front.math.ucdavis.edu/math.PR/0503008 (alternate)

3356. The Basic Representation of the Current Group O(n,1)^X in the L^2 space over the generalized Lebesgue Measure

Author(s): A.M.Vershik and M.I.Graev

Abstract: We give the realization of the representation of the current group O(n,1)^X where X is a manifold, in the Hilbert space of L^2(F,\nu) of functionals on the the space F of the generalized functions on the manifold X which are square integrable over measure \nu which is related to a distinguish Levy process with values in R^{n-1} which generalized one dimensional gamma process. Unipotent subgroup of the group O(n,1)^X acts as the group of multiplicators. Measure \nu is sigma-finite and invariant under the action current group O(n-1)^X. Ther case of n=2 (SL(2,R^X)) was considered before in the series of papers starting from the article Vershik-Gel'fand-Graev (1973).

http://arXiv.org/abs/math/0503404
http://front.math.ucdavis.edu/math.RT/0503404 (alternate)

3357. Dynamic importance sampling for uniformly recurrent markov chains

Author(s): Paul Dupuis and Hui Wang

Abstract: Importance sampling is a variance reduction technique for efficient estimation of rare-event probabilities by Monte Carlo. In standard importance sampling schemes, the system is simulated using an a priori fixed change of measure suggested by a large deviation lower bound analysis. Recent work, however, has suggested that such schemes do not work well in many situations. In this paper we consider dynamic importance sampling in the setting of uniformly recurrent Markov chains. By ``dynamic'' we mean that in the course of a single simulation, the change of measure can depend on the outcome of the simulation up till that time. Based on a control-theoretic approach to large deviations, the existence of asymptotically optimal dynamic schemes is demonstrated in great generality. The implementation of the dynamic schemes is carried out with the help of a limiting Bellman equation. Numerical examples are presented to contrast the dynamic and standard schemes.

http://arXiv.org/abs/math/0503454
http://front.math.ucdavis.edu/math.PR/0503454 (alternate)

3358. The exit problem for diffusions with time-periodic drift and stochastic resonance

Author(s): Samuel Herrmann and Peter Imkeller

Abstract: Physical notions of stochastic resonance for potential diffusions in periodically changing double-well potentials such as the spectral power amplification have proved to be defective. They are not robust for the passage to their effective dynamics: continuous-time finite-state Markov chains describing the rough features of transitions between different domains of attraction of metastable points. In the framework of one-dimensional diffusions moving in periodically changing double-well potentials we design a new notion of stochastic resonance which refines Freidlin's concept of quasi-periodic motion. It is based on exact exponential rates for the transition probabilities between the domains of attraction which are robust with respect to the reduced Markov chains. The quality of periodic tuning is measured by the probability for transition during fixed time windows depending on a time scale parameter. Maximizing it in this parameter produces the stochastic resonance points.

http://arXiv.org/abs/math/0503455
http://front.math.ucdavis.edu/math.PR/0503455 (alternate)

3359. Learning mixtures of separated nonspherical Gaussians

Author(s): Sanjeev Arora and Ravi Kannan

Abstract: Mixtures of Gaussian (or normal) distributions arise in a variety of application areas. Many heuristics have been proposed for the task of finding the component Gaussians given samples from the mixture, such as the EM algorithm, a local-search heuristic from Dempster, Laird and Rubin [J. Roy. Statist. Soc. Ser. B 39 (1977) 1-38]. These do not provably run in polynomial time. We present the first algorithm that provably learns the component Gaussians in time that is polynomial in the dimension. The Gaussians may have arbitrary shape, but they must satisfy a ``separation condition'' which places a lower bound on the distance between the centers of any two component Gaussians. The mathematical results at the heart of our proof are ``distance concentration'' results--proved using isoperimetric inequalities--which establish bounds on the probability distribution of the distance between a pair of points generated according to the mixture. We also formalize the more general problem of max-likelihood fit of a Gaussian mixture to unstructured data.

http://arXiv.org/abs/math/0503457
http://front.math.ucdavis.edu/math.PR/0503457 (alternate)

3360. Fast simulation of new coins from old

Author(s): Serban Nacu and Yuval Peres

Abstract: Let S\subset (0,1). Given a known function f:S\to (0,1), we consider the problem of using independent tosses of a coin with probability of heads p (where p\in S is unknown) to simulate a coin with probability of heads f(p). We prove that if S is a closed interval and f is real analytic on S, then f has a fast simulation on S (the number of p-coin tosses needed has exponential tails). Conversely, if a function f has a fast simulation on an open set, then it is real analytic on that set.

http://arXiv.org/abs/math/0503458
http://front.math.ucdavis.edu/math.PR/0503458 (alternate)

3361. Structure of large random hypergraphs

Author(s): R. W. R. Darling and J. R. Norris

Abstract: The theme of this paper is the derivation of analytic formulae for certain large combinatorial structures. The formulae are obtained via fluid limits of pure jump-type Markov processes, established under simple conditions on the Laplace transforms of their Levy kernels. Furthermore, a related Gaussian approximation allows us to describe the randomness which may persist in the limit when certain parameters take critical values. Our method is quite general, but is applied here to vertex identifiability in random hypergraphs. A vertex v is identifiable in n steps if there is a hyperedge containing v all of whose other vertices are identifiable in fewer steps. We say that a hyperedge is identifiable if every one of its vertices is identifiable. Our analytic formulae describe the asymptotics of the number of identifiable vertices and the number of identifiable hyperedges for a Poisson(\beta) random hypergraph \Lambda on a set V of N vertices, in the limit as N\to \infty. Here \beta is a formal power series with nonnegative coefficients \beta_0,\beta_1,..., and (\Lambda(A))_{A\subseteq V} are independent Poisson random variables such that \Lambda(A), the number of hyperedges on A, has mean N\beta_j/\pmatrixN j whenever |A|=j.

http://arXiv.org/abs/math/0503460
http://front.math.ucdavis.edu/math.PR/0503460 (alternate)

3362. Large deviations for template matching between point processes

Author(s): Zhiyi Chi

Abstract: We study the asymptotics related to the following matching criteria for two independent realizations of point processes X\sim X and Y\sim Y. Given l>0, X\cap [0,l) serves as a template. For each t>0, the matching score between the template and Y\cap [t,t+l) is a weighted sum of the Euclidean distances from y-t to the template over all y\in Y\cap [t,t+l). The template matching criteria are used in neuroscience to detect neural activity with certain patterns. We first consider W_l(\theta), the waiting time until the matching score is above a given threshold \theta. We show that whether the score is scalar- or vector-valued, (1/l)\log W_l(\theta) converges almost surely to a constant whose explicit form is available, when X is a stationary ergodic process and Y is a homogeneous Poisson point process. Second, as l\to\infty, a strong approximation for -\log [\Pr{W_l(\theta)=0}] by its rate function is established, and in the case where X is sufficiently mixing, the rates, after being centered and normalized by \sqrtl, satisfy a central limit theorem and almost sure invariance principle. The explicit form of the variance of the normal distribution is given for the case where X is a homogeneous Poisson process as well.

http://arXiv.org/abs/math/0503463
http://front.math.ucdavis.edu/math.PR/0503463 (alternate)

3363. Random k-SAT: Two Moments Suffice to Cross a Sharp Threshold

Author(s): Dimitris Achlioptas and Cristopher Moore

Abstract: Many NP-complete constraint satisfaction problems appear to undergo a "phase transition'' from solubility to insolubility when the constraint density passes through a critical threshold. In all such cases it is easy to derive upper bounds on the location of the threshold by showing that above a certain density the first moment (expectation) of the number of solutions tends to zero. We show that in the case of certain symmetric constraints, considering the second moment of the number of solutions yields nearly matching lower bounds for the location of the threshold. Specifically, we prove that the threshold for both random hypergraph 2-colorability (Property B) and random Not-All-Equal k-SAT is 2^{k-1} ln 2 -O(1). As a corollary, we establish that the threshold for random k-SAT is of order Theta(2^k), resolving a long-standing open problem.

http://arXiv.org/abs/cond-mat/0310227
http://front.math.ucdavis.edu/cond-mat/0310227 (alternate)

3364. Distribution of the Size of a Largest Planar Matching and Largest Planar Subgraph in Random Bipartite Graphs

Author(s): Marcos Kiwi and Martin Loebl

Abstract: We address the following question: When a randomly chosen regular bipartite multi--graph is drawn in the plane in the ``standard way'', what is the distribution of its maximum size planar matching (set of non--crossing disjoint edges) and maximum size planar subgraph (set of non--crossing edges which may share endpoints)? The problem is a generalization of the Longest Increasing Sequence (LIS) problem (also called Ulam's problem). We present combinatorial identities which relate the number of $r$-regular bipartite multi--graphs with maximum planar matching (maximum planar subgraph)of at most $d$ edges to a signed sum of restricted lattice walks in $\ZZ^d$, and to the number of pairs of standard Young tableaux of the same shape and with a ``descend--type'' property. Our results are obtained via generalizations of two combinatorial proofs through which Gessel's identity can be obtained (an identity that is crucial in the derivation of a bivariate generating function associated to the distribution of LISs, and key to the analytic attack on Ulam's problem).

http://arXiv.org/abs/math/0503465
http://front.math.ucdavis.edu/math.CO/0503465 (alternate)

3365. The Shannon information of filtrations and the additional logarithmic utility of insiders

Author(s): Stefan Ankirchner and Steffen Dereich and Peter Imkeller

Abstract: The background for the general mathematical link between utility and information theory investigated in this paper is a simple financial market model with two kinds of small traders: less informed traders and insiders, whose extra information is represented by an enlargement of the other agents' filtration. The expected logarithmic utility increment, i.e. the difference of the insider's and the less informed trader's expected logarithmic utility is described in terms of the information drift, i.e. the drift one has to eliminate in order to perceive the price dynamics as a martingale from the insider's perspective. On the one hand, we describe the information drift in a very general setting by natural quantities expressing the probabilistic better informed view of the world. This on the other hand allows us to identify the additional utility by entropy related quantities known from information theory. In particular, in a complete market in which the insider has some fixed additional information during the entire trading interval, its utility increment can be represented by the Shannon information of his extra knowledge. For general markets, and in some particular examples, we provide estimates of maximal utility by information inequalities.

http://arXiv.org/abs/math/0503013
http://front.math.ucdavis.edu/math.PR/0503013 (alternate)

3366. Diffusion maps, spectral clustering and reaction coordinates of dynamical systems

Author(s): Boaz Nadler and Stephane Lafon and Ronald R. Coifman and Ioannis G. Kevrekidis

Abstract: A central problem in data analysis is the low dimensional representation of high dimensional data, and the concise description of its underlying geometry and density. In the analysis of large scale simulations of complex dynamical systems, where the notion of time evolution comes into play, important problems are the identification of slow variables and dynamically meaningful reaction coordinates that capture the long time evolution of the system. In this paper we provide a unifying view of these apparently different tasks, by considering a family of {\em diffusion maps}, defined as the embedding of complex (high dimensional) data onto a low dimensional Euclidian space, via the eigenvectors of suitably defined random walks defined on the given datasets. Assuming that the data is randomly sampled from an underlying general probability distribution $p(\x)=e^{-U(\x)}$, we show that as the number of samples goes to infinity, the eigenvectors of each diffusion map converge to the eigenfunctions of a corresponding differential operator defined on the support of the probability distribution. Different normalizations of the Markov chain on the graph lead to different limiting differential operators. One normalization gives the Fokker-Planck operators with the same potential U(x), best suited for the study of stochastic differential equations as well as for clustering. Another normalization gives the Laplace-Beltrami (heat) operator on the manifold in which the data resides, best suited for the analysis of the geometry of the dataset, regardless of its possibly non-uniform density.

http://arXiv.org/abs/math/0503445
http://front.math.ucdavis.edu/math.NA/0503445 (alternate)

3367. Trading Strategy Adipted Optimization of European Call Option

Author(s): Toshio Fukumi

Abstract: Optimal pricing of European call option is described by linear stochastic differential equation. Trading strategy given by a twin of stochastic variables was integrated w.r.t. Black-Scholes formula to adopt optimal pricing to tarading strategy.

http://arXiv.org/abs/math/0503444
http://front.math.ucdavis.edu/math.OC/0503444 (alternate)

3368. Characterization of arbitrage-free markets

Author(s): Eva Strasser

Abstract: The present paper deals with the characterization of no-arbitrage properties of a continuous semimartingale. The first main result, Theorem \refMainTheoremCharNA, extends the no-arbitrage criterion by Levental and Skorohod [Ann. Appl. Probab. 5 (1995) 906-925] from diffusion processes to arbitrary continuous semimartingales. The second main result, Theorem 2.4, is a characterization of a weaker notion of no-arbitrage in terms of the existence of supermartingale densities. The pertaining weaker notion of no-arbitrage is equivalent to the absence of immediate arbitrage opportunities, a concept introduced by Delbaen and Schachermayer [Ann. Appl. Probab. 5 (1995) 926-945]. Both results are stated in terms of conditions for any semimartingales starting at arbitrary stopping times \sigma. The necessity parts of both results are known for the stopping time \sigma=0 from Delbaen and Schachermayer [Ann. Appl. Probab. 5 (1995) 926-945]. The contribution of the present paper is the proofs of the corresponding sufficiency parts.

http://arXiv.org/abs/math/0503473
http://front.math.ucdavis.edu/math.PR/0503473 (alternate)

3369. Gaussian limits for random measures in geometric probability

Author(s): Yu. Baryshnikov and J. E. Yukich

Abstract: We establish Gaussian limits for general measures induced by binomial and Poisson point processes in d-dimensional space. The limiting Gaussian field has a covariance functional which depends on the density of the point process. The general results are used to deduce central limit theorems for measures induced by random graphs (nearest neighbor, Voronoi and sphere of influence graph), random sequential packing models (ballistic deposition and spatial birth-growth models) and statistics of germ-grain models.

http://arXiv.org/abs/math/0503474
http://front.math.ucdavis.edu/math.PR/0503474 (alternate)

3370. On the distribution of the maximum of a gaussian field with d parameters

Author(s): Jean-Marc Azais and Mario Wschebor

Abstract: Let I be a compact d-dimensional manifold, let X:I\to R be a Gaussian process with regular paths and let F_I(u), u\in R, be the probability distribution function of sup_{t\in I}X(t). We prove that under certain regularity and nondegeneracy conditions, F_I is a C^1-function and satisfies a certain implicit equation that permits to give bounds for its values and to compute its asymptotic behavior as u\to +\infty. This is a partial extension of previous results by the authors in the case d=1. Our methods use strongly the so-called Rice formulae for the moments of the number of roots of an equation of the form Z(t)=x, where Z:I\to R^d is a random field and x is a fixed point in R^d. We also give proofs for this kind of formulae, which have their own interest beyond the present application.

http://arXiv.org/abs/math/0503475
http://front.math.ucdavis.edu/math.PR/0503475 (alternate)

3371. Heavy traffic analysis of open processing networks with complete resource pooling: asymptotic optimality of discrete review policies

Author(s): Baris Ata and Sunil Kumar

Abstract: We consider a class of open stochastic processing networks, with feedback routing and overlapping server capabilities, in heavy traffic. The networks we consider satisfy the so-called complete resource pooling condition and therefore have one-dimensional approximating Brownian control problems. We propose a simple discrete review policy for controlling such networks. Assuming 2+\epsilon moments on the interarrival times and processing times, we provide a conceptually simple proof of asymptotic optimality of the proposed policy.

http://arXiv.org/abs/math/0503477
http://front.math.ucdavis.edu/math.PR/0503477 (alternate)

3372. A Characterization of the optimal risk-Sensitive average cost in finite controlled Markov chains

Author(s): Rolando Cavazos-Cadena and Daniel Hernandez-Hernandez

Abstract: This work concerns controlled Markov chains with finite state and action spaces. The transition law satisfies the simultaneous Doeblin condition, and the performance of a control policy is measured by the (long-run) risk-sensitive average cost criterion associated to a positive, but otherwise arbitrary, risk sensitivity coefficient. Within this context, the optimal risk-sensitive average cost is characterized via a minimization problem in a finite-dimensional Euclidean space.

http://arXiv.org/abs/math/0503478
http://front.math.ucdavis.edu/math.PR/0503478 (alternate)

3373. Large deviations of the empirical volume fraction for stationary Poisson grain models

Author(s): Lothar Heinrich

Abstract: We study the existence of the (thermodynamic) limit of the scaled cumulant-generating function L_n(z)=|W_n|^{-1}\logE\exp{z|\Xi\cap W_n|} of the empirical volume fraction |\Xi\cap W_n|/|W_n|, where |\cdot| denotes the d-dimensional Lebesgue measure. Here \Xi=\bigcup_{i\ge1}(\Xi_i+X_i) denotes a d-dimensional Poisson grain model (also known as a Boolean model) defined by a stationary Poisson process \Pi_{\lambda}=\sum_{i\ge1}\delta_{X_i} with intensity \lambda >0 and a sequence of independent copies \Xi_1,\Xi_2,... of a random compact set \Xi_0. For an increasing family of compact convex sets {W_n, n\ge1} which expand unboundedly in all directions, we prove the existence and analyticity of the limit lim_{n\to\infty}L_n(z) on some disk in the complex plane whenever E\exp{a|\Xi_0|}<\infty for some a>0. Moreover, closely connected with this result, we obtain exponential inequalities and the exact asymptotics for the large deviation probabilities of the empirical volume fraction in the sense of Cram\'er and Chernoff.

http://arXiv.org/abs/math/0503479
http://front.math.ucdavis.edu/math.PR/0503479 (alternate)
stefano . iacus at unimi . it