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We present a Monte Carlo method to compute efficiently susceptibilites or covariances of two physical variables. The method relies on a generalization of the exchange cluster algorithm to any model of interacting particles with any $2$-body…

Computational Physics · Physics 2025-02-11 Assaraf Roland , Chevreau Hilaire

In statistical modeling of computer experiments sometimes prior information is available about the underlying function. For example, the physical system simulated by the computer code may be known to be monotone with respect to some or all…

Methodology · Statistics 2014-06-17 Shirin Golchi , Derek R. Bingham , Hugh Chipman , David A. Campbell

We obtain the analogue of the classical result by Erd\"os and Kac on the limiting distribution of the maximum of partial sums for exchangeable random variables with zero mean and variance one. We show that, if the conditions of the central…

Probability · Mathematics 2016-09-20 Patricia Alonso Ruiz , Alexander S. Rakitko

Beta regression is often used to model the relationship between a dependent variable that assumes values on the open interval (0,1) and a set of predictor variables. An important challenge in beta regression is to find residuals whose…

Methodology · Statistics 2017-04-11 Gustavo H. A. Pereira

In this paper, we introduce a new class of bivariate distributions by compounding the bivariate generalized exponential and power-series distributions. This new class contains some new sub-models such as the bivariate generalized…

Computation · Statistics 2015-08-04 Ali Akbar Jafari , Rasool Roozegar

In this paper, we discuss some theoretical results and properties of a discrete version of the Birnbaum-Saunders distribution. We present a proof of the unimodality of this model. Moreover, results on moments, quantile function, reliability…

Methodology · Statistics 2022-03-08 Filidor Vilca , Roberto Vila , Helton Saulo , Luis Sánchez , Jeremias Leão

Iterative imputation, in which variables are imputed one at a time each given a model predicting from all the others, is a popular technique that can be convenient and flexible, as it replaces a potentially difficult multivariate modeling…

Statistics Theory · Mathematics 2012-04-04 Jingchen Liu , Andrew Gelman , Jennifer Hill , Yu-Sung Su

We derive tests of stationarity for univariate time series by combining change-point tests sensitive to changes in the contemporary distribution with tests sensitive to changes in the serial dependence. The proposed approach relies on a…

Methodology · Statistics 2018-09-21 Axel Bücher , Jean-David Fermanian , Ivan Kojadinovic

This paper proposes a moving sum methodology for detecting multiple change points in high-dimensional time series under a factor model, where changes are attributed to those in loadings as well as emergence or disappearance of factors. We…

Methodology · Statistics 2025-07-24 Matteo Barigozzi , Haeran Cho , Lorenzo Trapani

In this work, Bernoulli's Law of Large Numbers, also known as the Golden theorem, has been extended to study the relations between empirical probability and empirical randomness of an otherwise random experiment. Using the example of a coin…

Data Analysis, Statistics and Probability · Physics 2025-06-04 Allen Lobo , Saravanan Arumugam

We develop approximate estimation methods for exponential random graph models (ERGMs), whose likelihood is proportional to an intractable normalizing constant. The usual approach approximates this constant with Monte Carlo simulations,…

Methodology · Statistics 2023-01-11 Angelo Mele , Lingjiong Zhu

We study a statistical model consisting of $N$ basic units which interact with each other by exchanging a physical entity, according to a given microscopic random law, depending on a parameter $\lambda$. We focus on the equilibrium or…

Statistical Mechanics · Physics 2009-11-10 Marco Patriarca , Anirban Chakraborti , Kimmo Kaski

We propose extensions and improvements of the statistical analysis of distributed multipoles (SADM) algorithm put forth by Chipot et al. in [6] for the derivation of distributed atomic multipoles from the quantum-mechanical electrostatic…

Numerical Analysis · Mathematics 2010-07-28 Nicolas Champagnat , Christophe Chipot , Erwan Faou

In this work, we deal with approximations for distribution functions of non-negative random variables. More specifically, we construct continuous approximants using an acceleration technique over a well-know inversion formula for Laplace…

Statistics Theory · Mathematics 2010-10-12 Carmen Sangüesa

We propose an algorithm for evaluation of the cumulative bivariate normal distribution, building upon Marsaglia's ideas for evaluation of the cumulative univariate normal distribution. The algorithm is mathematically transparent, delivers…

Numerical Analysis · Mathematics 2018-09-19 Christian Meyer

A new characterization of the exponential distribution is obtained. It is based on an equation involving randomly shifted (translated) order statistics. No specific distribution is assumed for the shift random variables. The proof uses a…

Probability · Mathematics 2017-01-05 Santanu Chakraborty , George P. Yanev

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

We investigate analytical properties of free stable distributions and discover many connections with their classical counterparts. Our main result is an explicit formula for the Mellin transform, which leads to explicit series…

Probability · Mathematics 2024-03-19 Takahiro Hasebe , Alexey Kuznetsov

We calculate the so-called Rademacher's Grand Lebesgue Space norm for a centered (shifted) indicator (Bernoulli's, binary) random variable. This norm is optimal for the centered and bounded random variables (r.v.). Using this result we…

Probability · Mathematics 2015-07-29 Eugene Ostrovsky , Leonid Sirota

Modeling binary and categorical data is one of the most commonly encountered tasks of applied statisticians and econometricians. While Bayesian methods in this context have been available for decades now, they often require a high level of…

Computation · Statistics 2023-07-03 Gregor Zens , Sylvia Frühwirth-Schnatter , Helga Wagner