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We present new Poisson process approximation results for stabilizing functionals of Poisson and binomial point processes. These functionals are allowed to have an unbounded range of interaction and encompass many examples in stochastic…

Probability · Mathematics 2021-04-28 Omer Bobrowski , Matthias Schulte , D. Yogeshwaran

We prove an exact fourth moment bound for the normal approximation of random variables belonging to the Wiener chaos of a general Poisson random measure. Such a result -- that has been elusive for several years -- shows that the so-called…

Probability · Mathematics 2021-04-01 Christian Döbler , Giovanni Peccati

We consider the Gaussian approximation for functionals of a Poisson process that are expressible as sums of region-stabilizing (determined by the points of the process within some specified regions) score functions and provide a bound on…

Probability · Mathematics 2022-09-20 Chinmoy Bhattacharjee , Ilya Molchanov

We explore two aspects of geometric approximation via a coupling approach to Stein's method. Firstly, we refine precision and increase scope for applications by convoluting the approximating geometric distribution with a simple translation…

Probability · Mathematics 2024-12-11 Fraser Daly , Claude Lefèvre

We study the accuracy of a scaled Poisson approximation to the weighted sum of independent Poisson random variables, focusing on in particular the relative error of the tail distribution. A bound on the relative approximation error is…

Probability · Mathematics 2024-03-18 Yue Tan , Yingdong Lu , Cathy Xia

Stein operators are differential operators which arise within the so-called Stein's method for stochastic approximation. We propose a new mechanism for constructing such operators for arbitrary (continuous or discrete) parametric…

Probability · Mathematics 2013-05-23 Christophe Ley , Yvik Swan

For any discrete target distribution, we exploit the connection between Markov chains and Stein's method via the generator approach and express the solution of Stein's equation in terms of expected hitting time. This yields new upper bounds…

Probability · Mathematics 2018-02-16 Michael C. H. Choi

In this article, we first obtain, for the Kolmogorov distance, an error bound between a tempered stable and a compound Poisson distribution and also an error bound between a tempered stable and an alpha stable distribution via Stein method.…

Probability · Mathematics 2024-08-20 Kalyan Burman , Neelesh S Upadhye , Palaniappan Vellaisamy

We establish various bounds on the solutions to a Stein equation for Poisson approximation in Wasserstein distance with non-linear transportation costs. The proofs are a refinement of those in [Barbour and Xia (2006)] using the results in…

Probability · Mathematics 2020-04-01 Zhong-Wei Liao , Yutao Ma , Aihua Xia

Let F ($\nu$) be the centered Gamma law with parameter $\nu$ > 0 and let us denote by P Y the probability distribution of a random vector Y. We develop a multidimensional variant of the Stein's method for Gamma approximation that allows to…

Probability · Mathematics 2023-05-10 Ciprian A Tudor , Jérémy Zurcher

This exposition explains the basic ideas of Stein's method for Poisson random variable approximation and Poisson process approximation from the point of view of the immigration-death process and Palm theory. The latter approach also enables…

Probability · Mathematics 2007-05-23 Louis H. Y. Chen , Aihua Xia

This paper uses the generator approach of Stein's method to analyze the gap between steady-state distributions of Markov chains and diffusion processes. Until now, the standard way to invoke Stein's method for this problem was to use the…

Probability · Mathematics 2022-02-15 Anton Braverman

This paper uses the generator comparison approach of Stein's method to analyze the gap between steady-state distributions of Markov chains and diffusion processes. The "standard" generator comparison approach starts with the Poisson…

Probability · Mathematics 2021-10-11 Anton Braverman

Let $X_1,\ldots,X_n$ be a sequence of independent random points in $\mathbb{R}^d$ with common Lebesgue density $f$. Under some conditions on $f$, we obtain a Poisson limit theorem, as $n \to \infty$, for the number of large probability…

Probability · Mathematics 2021-05-04 Nicolas Chenavier , Norbert Henze , Moritz Otto

A fundamental problem in numerical analysis and approximation theory is approximating smooth functions by polynomials. A much harder version under recent consideration is to enforce bounds constraints on the approximating polynomial. In…

Numerical Analysis · Mathematics 2021-12-28 Larry Allen , Robert C. Kirby

Friedman's chi-square test is a non-parametric statistical test for $r\geq2$ treatments across $n\ge1$ trials to assess the null hypothesis that there is no treatment effect. We use Stein's method with an exchangeable pair coupling to…

Statistics Theory · Mathematics 2022-07-01 Robert E. Gaunt , Gesine Reinert

Motivated by its appearance as a limiting distribution for random and non-random sums of independent random variables, in this paper we develop Stein's method for approximation by the asymmetric Laplace distribution. Our results generalise…

Probability · Mathematics 2026-05-15 Fraser Daly , Robert E. Gaunt , Heather L. Sutcliffe

New lower bounds on the total variation distance between the distribution of a sum of independent Bernoulli random variables and the Poisson random variable (with the same mean) are derived via the Chen-Stein method. The new bounds rely on…

Information Theory · Computer Science 2013-07-17 Igal Sason

Applying an inductive technique for Stein and zero bias couplings yields Berry-Esseen theorems for normal approximation for two new examples. The conditions of the main results do not require that the couplings be bounded. Our two…

Probability · Mathematics 2020-05-12 Louis H. Y. Chen , Larry Goldstein , Adrian Röllin

Multivariate Poisson approximation of the length spectrum of random surfaces is studied by means of the Chen-Stein method. This approach delivers simple and explicit error bounds in Poisson limit theorems. They are used to prove that…

Probability · Mathematics 2017-11-28 Bram Petri , Christoph Thaele