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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

Competing and Complementary risk (CCR) problems are often modelled using a class of distributions of the maximum, or minimum, of a random number of i.i.d. random variables; we call this class the CCR class of distributions. While the CCR…

Probability · Mathematics 2025-10-21 Anum Fatima , Gesine Reinert

This paper derives lower bounds for the mean square errors of parameter estimators in the case of Poisson distributed data subjected to multiple abrupt changes. Since both change locations (discrete parameters) and parameters of the Poisson…

Information Theory · Computer Science 2016-10-31 Lucien Bacharach , Mohammed Nabil El Korso , Alexandre Renaux , Jean-Yves Tourneret

We obtain upper bounds for the total variation distance between the distributions of two Gibbs point processes in a very general setting. Applications are provided to various well-known processes and settings from spatial statistics and…

Probability · Mathematics 2014-09-15 Dominic Schuhmacher , Kaspar Stucki

We study the approximation of a Markov chain on a reduced state space, for both discrete- and continuous-time Markov chains. In this context, we extend the existing theory of formal error bounds for the approximated transient distributions.…

Probability · Mathematics 2025-02-12 Fabian Michel , Markus Siegle

A Cram\'er-type moderate deviation theorem quantifies the relative error of the tail probability approximation. It provides theoretical justification when the limiting tail probability can be used to estimate the tail probability under…

Probability · Mathematics 2021-04-28 Qi-Man Shao , Mengchen Zhang , Zhuo-Song Zhang

We consider Linear Stochastic Approximation (LSA) with a constant stepsize and Markovian data. Viewing the joint process of the data and LSA iterate as a time-homogeneous Markov chain, we prove its convergence to a unique limiting and…

Machine Learning · Statistics 2026-01-21 Dongyan Huo , Yudong Chen , Qiaomin Xie

Consider a population of individuals belonging to an infinity number of types, and assume that type proportions follow the two-parameter Poisson-Dirichlet distribution. A sample of size n is selected from the population. The total number of…

Probability · Mathematics 2016-10-12 Stefano Favaro , Shui Feng , Fuqing Gao

We analyze the Gaussian approximation as a method to obtain the first and second moments of a stochastic process described by a master equation. We justify the use of this approximation with ideas coming from van Kampen's expansion approach…

Statistical Mechanics · Physics 2015-05-18 Luis F. Lafuerza , Raul Toral

A basic condition for efficient transfer learning is the similarity between a target model and source models. In practice, however, the similarity condition is difficult to meet or is even violated. Instead of the similarity condition, a…

Machine Learning · Statistics 2022-06-14 Lu Lin , Weiyu Li

The (conditional or unconditional) distribution of the continuous scan statistic in a one-dimensional Poisson process may be approximated by that of a discrete analogue via time discretization (to be referred to as the discrete…

Probability · Mathematics 2016-02-09 Yi-Ching Yao , Daniel Wei-Chung Miao , Xenos Chang-Shuo Lin

We present a theoretical analysis of stochastic optimization methods in terms of their sensitivity with respect to the step size. We identify a key quantity that, for each method, describes how the performance degrades as the step size…

Optimization and Control · Mathematics 2026-05-27 Fabian Schaipp , Robert M. Gower , Adrien Taylor

We develop a framework for the compression of reversible Markov chains with rigorous error control. Given a subset of selected states, we construct reduced dynamics that can be lifted to an approximation of the full dynamics, and we prove…

Numerical Analysis · Mathematics 2025-09-03 Mark Fornace , Michael Lindsey

The solution to Poisson's equation arise in many Markov chain and Markov jump process settings, including that of the central limit theorem, value functions for average reward Markov decision processes, and within the gradient formula for…

Probability · Mathematics 2024-01-30 Saied Mahdian , Peter W. Glynn , Yuanyuan Liu

Consider a finite irreducible Markov chain with invariant distribution $\pi$. We use the inner product induced by $\pi$ and the associated heat operator to simplify and generalize some results related to graph partitioning and the small-set…

Data Structures and Algorithms · Computer Science 2013-11-05 Ryan O'Donnell , David Witmer

The paper studies an improved estimate for the rate of convergence for nonlinear homogeneous discrete-time Markov chains. These processes are nonlinear in terms of the distribution law. Hence, the transition kernels are dependent on the…

Probability · Mathematics 2021-05-21 Aleksandr Shchegolev

We consider whether ergodic Markov chains with bounded step size remain bounded in probability when their transitions are modified by an adversary on a bounded subset. We provide counterexamples to show that the answer is no in general, and…

The statistical distribution of levels of an integrable system is claimed to be a Poisson distribution. In this paper, we numerically generate an ensemble of N dimensional random diagonal matrices as a model for regular systems. We evaluate…

Exactly Solvable and Integrable Systems · Physics 2011-09-27 A. A. Abul-Magd , A. Y. Abul-Magd

Consider a uniformly chosen random reduced decomposition of the longest element in the symmetric group. It is known that the location of the first transposition in this decomposition converges to the semicircle distribution. In this note we…

Probability · Mathematics 2014-05-07 Jason Fulman , Larry Goldstein

We consider decision problems on finite sets of hypotheses represented by pairwise different shift-invariant states on a quantum spin chain. The decision in favor of one of the hypotheses is based on outputs of generalized measurements…

Quantum Physics · Physics 2015-05-18 Michael Nussbaum , Arleta Szkola
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