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This article shows how coupled Markov chains that meet exactly after a random number of iterations can be used to generate unbiased estimators of the solutions of the Poisson equation. Through this connection, we re-derive known unbiased…

Computation · Statistics 2025-12-10 Randal Douc , Pierre E. Jacob , Anthony Lee , Dootika Vats

The two-parameter Poisson--Dirichlet distribution is a probability distribution on the totality of positive decreasing sequences with sum 1 and hence considered to govern masses of a random discrete distribution. A characterization of the…

Probability · Mathematics 2010-01-12 Kenji Handa

We study fundamental properties of the gamma process and their relation to various topics such as Poisson-Dirichlet measures and stable processes. We prove the quasi-invariance of the gamma process with respect to a large group of linear…

Probability · Mathematics 2007-05-23 N. Tsilevich , A. Vershik , M. Yor

Conditions on the generator of a Markov process to control the fluctuations of its bridges are found. In particular, continuous time random walks on graphs and gradient diffusions are considered. Under these conditions, a concentration of…

Probability · Mathematics 2016-03-08 Giovanni Conforti

We consider a class of semi-Markov processes (SMP) such that the embedded discrete time Markov chain may be non-homogeneous. The corresponding augmented processes are represented as semi-martingales using stochastic integral equation…

Probability · Mathematics 2022-07-14 Anindya Goswami , Subhamay Saha , Ravishankar Kapildev Yadav

MCMC methods (Monte Carlo Markov Chain) are a class of methods used to perform simulations per a probability distribution $P$. These methods are often used when we have difficulties to directly sample per a given probability distribution…

Methodology · Statistics 2014-01-21 Papa Ngom , Badiassiatta Don Bosco Diatta

Let $(X_n)$ be a Markov chain on a standard borelian space $\mathbb{X}$. Any stopping time $\tau$ such that $\mathbb{E}_x\tau$ is finite for all $x\in\mathbb{X}$ induces a Markov chain in $\mathbb{X}$. In this article, we show that there is…

Probability · Mathematics 2015-06-26 Jean-Baptiste Boyer

Let $Y=(y_1,y_2,...)$, $y_1\ge y_2\ge...$, be the list of sizes of the cycles in the composition of $c n$ transpositions on the set $\{1,2,...,n\}$. We prove that if $c>1/2$ is constant and $n\to\infty$, the distribution of $f(c)Y/n$…

Probability · Mathematics 2007-07-04 Oded Schramm

We equip the polytope of $n\times n$ Markov matrices with the normalized trace of the Lebesgue measure of $\mathbb{R}^{n^2}$. This probability space provides random Markov matrices, with i.i.d. rows following the Dirichlet distribution of…

Probability · Mathematics 2010-06-16 Djalil Chafai

We investigate a piecewise-deterministic Markov process, evolving on a Polish metric space, whose deterministic behaviour between random jumps is governed by some semi-flow, and any state right after the jump is attained by a randomly…

Probability · Mathematics 2020-12-04 Dawid Czapla , Sander C. Hille , Katarzyna Horbacz , Hanna Wojewódka-Ściążko

We study a limit behavior of a sequence of Markov processes (or Markov chains) such that their distributions outside of any neighborhood of a "singular" point attract to some probability law. In any neighborhood of this point the behavior…

Probability · Mathematics 2015-09-14 Andrey Pilipenko , Yuriy Prykhodko

We define a general class of random systems of horizontal and vertical weighted broken lines on the quarter plane whose distribution are proved to be translation invariant. This invariance stems from a reversibility property of the model.…

Probability · Mathematics 2022-10-10 Alexandre Boyer , Jérôme Casse , Nathanaël Enriquez , Arvind Singh

A multiplicative cascade can be thought of as a randomization of a measure on the boundary of a tree, constructed from an iid collection of random variables attached to the tree vertices. Given an initial measure with certain regularity…

Probability · Mathematics 2013-05-28 Tom Alberts , Ben Rifkind

We consider a Markov chain on $\mathbb{R}^d$ with invariant measure $\mu$. We are interested in the rate of convergence of the empirical measures towards the invariant measure with respect to various dual distances, including in particular…

Probability · Mathematics 2022-10-13 Adrian Riekert

Consider a probability measure supported by a regular geodesic ball in a manifold. For any p larger than or equal to 1 we define a stochastic algorithm which converges almost surely to the p-mean of the measure. Assuming furthermore that…

Probability · Mathematics 2011-06-28 Marc Arnaudon , Clément Dombry , Anthony Phan , Le Yang

We study existence and uniqueness of invariant probability measures for continuous-time Markov processes on general state spaces. Existence is obtained from tightness of time averages under a weak regularity assumption inspired by…

Probability · Mathematics 2026-01-21 Jean-Gabriel Attali

The notion of a successful coupling of Markov processes, based on the idea that both components of the coupled system ``intersect'' in finite time with probability one, is extended to cover situations when the coupling is unnecessarily…

Probability · Mathematics 2007-05-23 Michael Blank , Sergey Pirogov

A piecewise-deterministic Markov process, specified by random jumps and switching semi-flows, as well as the associated Markov chain given by its post-jump locations, are investigated in this paper. The existence of an exponentially…

Probability · Mathematics 2020-12-07 Dawid Czapla , Katarzyna Horbacz , Hanna Wojewódka-Ściążko

We consider the asymptotics of the invariant measure for the process of the empirical spatial distribution of $N$ coupled Markov chains in the limit of a large number of chains. Each chain reflects the stochastic evolution of one particle.…

Probability · Mathematics 2013-01-25 Vivek S. Borkar , Rajesh Sundaresan

We consider two examples for a well-known method for obtaining concentration of measure (COM) bounds for a given observable in a given measure. The method is to consider an auxiliary Markov chain for which the invariant distribution is the…

Probability · Mathematics 2019-01-25 Michael Froehlich , Shannon Starr