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Popular deterministic approximations of posterior distributions from, e.g. the Laplace method, variational Bayes and expectation-propagation, generally rely on symmetric approximating families, often taken to be Gaussian. This choice…

Methodology · Statistics 2026-01-19 Francesco Pozza , Daniele Durante , Botond Szabo

This paper introduces constrained mixtures for continuous distributions, characterized by a mixture of distributions where each distribution has a shape similar to the base distribution and disjoint domains. This new concept is used to…

Machine Learning · Statistics 2015-03-29 Conrado S. Miranda , Fernando J. Von Zuben

Sampling from multimodal distributions is a challenging task in scientific computing. When a distribution has an exact symmetry between the modes, direct jumps among them can accelerate the samplings significantly. However, the…

Numerical Analysis · Mathematics 2024-01-05 Lexing Ying

Stein's method is used to approximate sums of discrete and locally dependent random variables by a centered and symmetric Binomial distribution. Under appropriate smoothness properties of the summands, the same order of accuracy as in the…

Probability · Mathematics 2007-05-23 Adrian Röllin

Many approximate Bayesian inference methods assume a particular parametric form for approximating the posterior distribution. A multivariate Gaussian distribution provides a convenient density for such approaches; examples include the…

Methodology · Statistics 2023-02-20 Jackson Zhou , Clara Grazian , John Ormerod

We give a simple polynomial-time approximation algorithm for the total variation distance between two product distributions.

Data Structures and Algorithms · Computer Science 2024-02-14 Weiming Feng , Heng Guo , Mark Jerrum , Jiaheng Wang

We revisit the proof of the de Moivre--Laplace theorem, which is the ancestor of the central limit theorem for the binomial distribution. Our goal is to provide a proof that can be reasonably presented to undergraduate students within a…

Probability · Mathematics 2025-12-30 Raphaël Cerf

We approximate the distribution of the sum of independent but not necessarily identically distributed Bernoulli random variables using a shifted binomial distribution where the three parameters (the number of trials, the probability of…

Probability · Mathematics 2010-04-02 Vydas Čekanavičius , Erol A. Peköz , Adrian Röllin , Michael Shwartz

Distribution of the sum of independent identically distributed symmetric lattice vectors is approximated by the accompanying compound Poisson law and the second-order Hipp-type signed compound Poisson measure. Bergstr\"om -type asymptotic…

Probability · Mathematics 2026-05-22 Vydas Čekanavičius , Simona Jokubauskienė

This paper examines the classical matching distribution arising in the "problem of coincidences". We generalise the classical matching distribution with a preliminary round of allocation where items are correctly matched with some fixed…

Other Statistics · Statistics 2021-12-24 Ben O'Neill

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

In this paper we develop a very general class of bivariate discrete distributions. The basic idea is very simple. The marginals are obtained by taking the random geometric sum of a baseline distribution function. The proposed class of…

Methodology · Statistics 2018-05-22 Debasis Kundu

We are interested in comparing probability distributions defined on Riemannian manifold. The traditional approach to study a distribution relies on locating its mean point and finding the dispersion about that point. On a general manifold…

Statistics Theory · Mathematics 2008-07-22 Nikolay H. Balov

Bounds of the accuracy of the normal approximation to the distribution of a sum of independent random variables are improved under relaxed moment conditions, in particular, under the absence of moments of orders higher than the second.…

Probability · Mathematics 2015-07-06 V. Yu. Korolev , A. V. Dorofeeva

We consider the nearest-neighbor spacing distributions of mixed random matrix ensembles interpolating between different symmetry classes, or between integrable and non-integrable systems. We derive analytical formulas for the spacing…

Mathematical Physics · Physics 2012-08-22 Sebastian Schierenberg , Falk Bruckmann , Tilo Wettig

Two approaches are suggested to the definition of asymmetric generalized Weibull distribution. These approaches are based on the representation of the two-sided Weibull distributions as variance-mean normal mixtures or more general…

Probability · Mathematics 2015-06-23 Victor Korolev , Lily Kurmangazieva , Alexander Zeifman

We consider the problem of uniform sampling of points on an algebraic variety. Specifically, we develop a randomized algorithm that, given a small set of multivariate polynomials over a sufficiently large finite field, produces a common…

Data Structures and Algorithms · Computer Science 2009-02-10 Mahdi Cheraghchi , Amin Shokrollahi

The distribution of sum of independent non-identical binomial random variables is frequently encountered in areas such as genomics, healthcare, and operations research. Analytical solutions to the density and distribution are usually…

Computation · Statistics 2017-12-06 Boxiang Liu , Thomas Quertermous

The Conway-Maxwell-Poisson (CMP) distribution is a natural two-parameter generalisation of the Poisson distribution which has received some attention in the statistics literature in recent years by offering flexible generalisations of some…

Probability · Mathematics 2017-03-17 Fraser Daly , Robert E. Gaunt

This paper considers the approximation of a monomial $x^n$ over the interval $[-1,1]$ by a lower-degree polynomial. This polynomial approximation can be easily computed analytically and is obtained by truncating the analytical Chebyshev…

Numerical Analysis · Mathematics 2021-01-19 Arvind K. Saibaba
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