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We consider a discrete-time random walk on the nodes of an unbounded hexagonal lattice. We determine the probability generating functions, the transition probabilities and the relevant moments. The convergence of the stochastic process to a…

Probability · Mathematics 2019-09-16 Antonio Di Crescenzo , Claudio Macci , Barbara Martinucci , Serena Spina

The stochastic properties of a Langevin-type Markov process can be extracted from a given time series by a Markov analysis. Also processes that obey a stochastically forced second order differential equation can be analyzed this way by…

Data Analysis, Statistics and Probability · Physics 2014-12-09 Bernd Lehle , Joachim Peinke

We consider additive functionals of stationary Markov processes and show that under Kipnis-Varadhan type conditions they converge in rough path topology to a Stratonovich Brownian motion, with a correction to the Levy area that can be…

Probability · Mathematics 2019-12-23 Jean-Dominique Deuschel , Tal Orenshtein , Nicolas Perkowski

We propose a new method to apply the Lipschitz functional calculus of local Dirichlet forms to Poisson random measures.

Probability · Mathematics 2008-09-03 Nicolas Bouleau

We present order of magnitude estimates for the quantiles of non-negative linear combinations of non-negative random variables, as well as deviation inequalities for general linear combinations of independent random variables, under the…

Probability · Mathematics 2022-08-17 Daniel J. Fresen

In this paper, we present methods of obtaining single moments of order statistics arising from posibly dependent and non-identically distributed discrete random variables. We derive exact and approximate formulas convenient for numerical…

Probability · Mathematics 2019-11-28 Anna Dembińska , Agnieszka Goroncy

Let X_1 ,..., X_n be a collection of binary valued random variables and let f : {0,1}^n -> R be a Lipschitz function. Under a negative dependence hypothesis known as the {\em strong Rayleigh} condition, we show that f - E f satisfies a…

Probability · Mathematics 2013-07-30 Robin Pemantle , Yuval Peres

We obtain a condition for the $L^q$-convergence of martingales generated by random multiplicative cascade measures for $q>1$ without any self-similarity requirements on the cascades.

Probability · Mathematics 2013-11-04 K. J. Falconer

We derive exponential bounds on probabilities of large deviations for "light tail" martingales taking values in finite-dimensional normed spaces. Our primary emphasis is on the case where the bounds are dimension-independent or nearly so.…

Probability · Mathematics 2023-01-31 Anatoli Juditsky , Arkadii S. Nemirovski

Hamiltonians that are multivalued functions of momenta are of topical interest since they correspond to the Lagrangians containing higher-degree time derivatives. Incidentally, such classes of branched Hamiltonians lead to certain not too…

Mathematical Physics · Physics 2017-06-01 Bijan Bagchi , Syed M. Kamil , Tarun R. Tummuru , Iveta Semoradova , Miloslav Znojil

We establish a Large Deviations Principle for stochastic processes with Lipschitz continuous oblique reflections on regular domains. The rate functional is given as the value function of a control problem and is proved to be good. The proof…

Probability · Mathematics 2010-12-14 Magdalena Kobylanski

In this paper we study a family of nonlinear (conditional) expectations that can be understood as a continuous semimartingale with uncertain local characteristics. Here, the differential characteristics are prescribed by a set-valued…

Probability · Mathematics 2023-08-04 David Criens , Lars Niemann

In this paper, under a one-sided Lipschitz condition on the drift coefficient we adopt (via contraction principle) a exponential approximation argument to investigate large deviations for neutral stochastic functional differential…

Probability · Mathematics 2019-03-18 Yongqiang Suo , Chenggui Yuan

We present a numerical method to compute expectations of functionals of a piecewise-deterministic Markov process. We discuss time dependent functionals as well as deterministic time horizon problems. Our approach is based on the…

Probability · Mathematics 2012-01-31 Adrien Brandejsky , Benoîte de Saporta , François Dufour

Large deviations for additive path functionals of stochastic processes have attracted significant research interest, in particular in the context of stochastic particle systems and statistical physics. Efficient numerical `cloning'…

Probability · Mathematics 2021-07-21 Letizia Angeli , Stefan Grosskinsky , Adam M. Johansen

This note provides several recent progresses in the study of long time behavior of Markov processes. The examples presented below are related to other scientific fields as PDE's, physics or biology. The involved mathematical tools as…

Probability · Mathematics 2015-07-22 Florian Bouguet , Florent Malrieu , Fabien Panloup , Christophe Poquet , Julien Reygner

Monotone L\'evy processes with additive increments are defined and studied. It is shown that these processes have a natural Markov structure and their Markov transition semigroups are characterized using the monotone L\'evy-Khintchine…

Probability · Mathematics 2021-04-21 Uwe Franz , Naofumi Muraki

Random walk is one of the most classical and well-studied model in probability theory. For two correlated random walks on lattice, every step of the random walks has only two states, moving in the same direction or moving in the opposite…

Probability · Mathematics 2018-08-17 Tianyao Chen , Xue Cheng , Jingping Yang

In this paper we provide a rigorous mathematical foundation for continuous approximations of a class of systems with piece-wise continuous functions. By using techniques from the theory of differential inclusions, the underlying piece-wise…

Chaotic Dynamics · Physics 2014-08-20 Marius-F. Danca

We introduce a non-homogeneous fractional Poisson process by replacing the time variable in the fractional Poisson process of renewal type with an appropriate function of time. We characterize the resulting process by deriving its non-local…

Probability · Mathematics 2016-01-18 N. Leonenko , E. Scalas , M. Trinh