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We study a general non-homogeneous Skellam-type process with jumps of arbitrary fixed size. We express this process in terms of a linear combination of Poisson processes and study several properties, including the summation of independent…

Probability · Mathematics 2025-04-11 Fabrizio Cinque , Enzo Orsingher

Certain monotonicity properties of the Poisson approximation to the binomial distribution are established. As a natural application of these results, exact (rather than approximate) tests of hypotheses on an unknown value of the parameter…

Probability · Mathematics 2020-08-05 Iosif Pinelis

We discuss a thinning and an embedding procedure to construct finite Gibbs processes with a given Papangelou intensity. Extending the approach in Hofer-Temmel (2019) and Hofer-Temmel and Houdebert (2019) we will use this to couple two…

Probability · Mathematics 2023-01-24 Günter Last , Moritz Otto

In this paper we present multivariate space-time fractional Poisson processes by considering common random time-changes of a (finite-dimensional) vector of independent classical (non-fractional) Poisson processes. In some cases we also…

Probability · Mathematics 2015-07-22 Luisa Beghin , Claudio Macci

Many random combinatorial objects have a component structure whose joint distribution is equal to that of a process of mutually independent random variables, conditioned on the value of a weighted sum of the variables. It is interesting to…

Probability · Mathematics 2013-08-16 Richard Arratia , Simon Tavare

The randomized $k$-number partitioning problem is the task to distribute $N$ i.i.d. random variables into $k$ groups in such a way that the sums of the variables in each group are as similar as possible. The restricted $k$-partitioning…

Disordered Systems and Neural Networks · Physics 2007-05-23 Anton Bovier , Irina Kurkova

Gaussian couplings of partial sum processes are derived for the high-dimensional regime $d=o(n^{1/3})$. The coupling is derived for sums of independent random vectors and subsequently extended to nonstationary time series. Our inequalities…

Probability · Mathematics 2022-03-08 Fabian Mies , Ansgar Steland

In this paper, we extend the notion of Cauchy-Schwarz divergence to point processes and establish that the Cauchy-Schwarz divergence between the probability densities of two Poisson point processes is half the squared…

Information Theory · Computer Science 2015-07-21 Hung Gia Hoang , Ba-Ngu Vo , Ba-Tuong Vo , Ronald Mahler

In this paper, we precisely quantify the wavelet compressibility of compound Poisson processes. To that end, we expand the given random process over the Haar wavelet basis and we analyse its asymptotic approximation properties. By only…

Information Theory · Computer Science 2021-12-20 Shayan Aziznejad , Julien Fageot

We generalize the Poisson limit theorem to binary functions of random objects whose law is invariant under the action of an amenable group. Examples include stationary random fields, exchangeable sequences, and exchangeable graphs. A…

Probability · Mathematics 2024-01-19 Haoyu Ye , Peter Orbanz , Morgane Austern

Different change-point type models encountered in statistical inference for stochastic processes give rise to different limiting likelihood ratio processes. In this paper we consider two such likelihood ratios. The first one is an…

Statistics Theory · Mathematics 2010-04-05 Serguei Dachian

We introduce a semi-implicit Euler-Maruyama approximation which preservers the non-colliding property for some class of non-colliding particle systems such as Dyson Brownian motions, Dyson-Ornstein-Uhlenbeck processes and Brownian particles…

Probability · Mathematics 2018-05-17 Hoang-Long Ngo , Dai Taguchi

We consider a type of nonnormal approximation of infinitely divisible distributions that incorporates compound Poisson, Gamma, and normal distributions. The approximation relies on achieving higher orders of cumulant matching, to obtain…

Probability · Mathematics 2013-04-24 Zhiyi Chi

An information-theoretic development is given for the problem of compound Poisson approximation, which parallels earlier treatments for Gaussian and Poisson approximation. Let $P_{S_n}$ be the distribution of a sum $S_n=\Sumn Y_i$ of…

Probability · Mathematics 2019-06-05 A. D. Barbour , Oliver Johnson , Ioannis Kontoyiannis , Mokshay Madiman

A thorough account is given of the derivation of uniform semiclassical approximations to the particle and kinetic energy densities of N noninteracting bounded fermions in one dimension. The employed methodology allows the inclusion of…

Quantum Physics · Physics 2015-10-21 Raphael F. Ribeiro , Kieron Burke

We develop a pseudo-metric analogue of bisimulation for generalized semi-Markov processes. The kernel of this pseudo-metric corresponds to bisimulation; thus we have extended bisimulation for continuous-time probabilistic processes to a…

Logic in Computer Science · Computer Science 2017-01-11 Vineet Gupta , Radha Jagadeesan , Prakash Panangaden

Poisson approximation using Stein's method has been extensively studied in the literature. The main focus has been on bounding the total variation distance. This paper is a first attempt on moderate deviations in Poisson approximation for…

Probability · Mathematics 2013-06-21 Louis H. Y. Chen , Xiao Fang , Qi-Man Shao

The idea behind Poisson approximation to the binomial distribution was used in [J. de la Cal, F. Luquin, J. Approx. Theory, 68(3), 1992, 322-329] and subsequent papers in order to establish the convergence of suitable sequences of positive…

Probability · Mathematics 2022-08-18 Ana-Maria Acu , Margareta Heilmann , Ioan Rasa , Andra Seserman

We present a random walk approximation to fractional Brownian motion where the increments of the fractional random walk are defined as a weighted sum of the past increments of a Bernoulli random walk.

Probability · Mathematics 2007-08-15 Tom Lindstrøm

Non-uniform estimates are obtained for Poisson, compound Poisson, translated Poisson, negative binomial and binomial approximations to sums of of m-dependent integer-valued random variables. Estimates for Wasserstein metric also follow…

Probability · Mathematics 2014-08-19 P. Vellaisamy , V. Cekanavicius