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We introduce a new class of multivariate elliptically symmetric distributions including elliptically symmetric logistic distributions and Kotz type distributions. We investigate the various probabilistic properties including marginal…

Statistics Theory · Mathematics 2020-08-04 Yeshunying Wang , Chuancun Yin

The upper bound inequality for variance of weighted sum of correlated random variables is derived according to Cauchy-Schwarz's inequality, while the weights are non-negative with sum of 1. We also give a novel proof with positive…

Probability · Mathematics 2014-12-18 Jingwei Liu

In this paper non-asymptotic exact rearrangement invariant norm estimates are derived for the maximum distribution of the family elements of some rearrangement invariant (r.i.) space over unbounded measure in the entropy terms and in the…

Functional Analysis · Mathematics 2008-08-26 E. Ostrovsky , E. Rogover

We present new sampling methods in finite population that allow to control the joint inclusion probabilities of units and especially the spreading of sampled units in the population. They are based on the use of renewal chains and…

Methodology · Statistics 2017-04-12 Yves Tillé , Lionel Qualité , Matthieu Wilhelm

In this manuscript, we study the limiting distribution for the joint law of the largest and the smallest singular values for random circulant matrices with generating sequence given by independent and identically distributed random elements…

Probability · Mathematics 2023-05-05 Gerardo Barrera , Paulo Manrique-Mirón

Fluctuations of global additive quantities, like total energy or magnetization for instance, can in principle be described by statistics of sums of (possibly correlated) random variables. Yet, it turns out that extreme values (the largest…

Statistical Mechanics · Physics 2008-11-18 Maxime Clusel , Eric Bertin

We derive the distribution of the ratio of a non-central mean matrix and a sample covariance matrix. This aligns with the confluent term ${}_1F_1$ in the non-central uni-variate Student's $t$. Some extensions of matrix-variate distributions…

Statistics Theory · Mathematics 2026-04-24 Haoming Wang

Ratio statistics and distributions are fundamental in various disciplines, including linear regression, metrology, nuclear physics, operations research, econometrics, biostatistics, genetics, and engineering. In this work, we introduce two…

Computation · Statistics 2025-06-24 Jozef Hanč , Martina Hančová , Dominik Borovský

Given a distribution $\rho$ on persistence diagrams and observations $X_1,...X_n \stackrel{iid}{\sim} \rho$ we introduce an algorithm in this paper that estimates a Fr\'echet mean from the set of diagrams $X_1,...X_n$. If the underlying…

Statistics Theory · Mathematics 2013-03-21 Katharine Turner , Yuriy Mileyko , Sayan Mukherjee , John Harer

In this paper, an optimization problem with uncertain constraint coefficients is considered. Possibility theory is used to model the uncertainty. Namely, a joint possibility distribution in constraint coefficient realizations, called…

Optimization and Control · Mathematics 2023-09-07 Romain Guillaume , Adam Kasperski , Pawel Zielinski

This paper proposes to unify fading distributions by modeling the magnitude-squared of the instantaneous channel gain as an infinitely divisible random variable. A random variable is said to be infinitely divisible, if it can be written as…

Information Theory · Computer Science 2015-08-21 Adithya Rajan , Cihan Tepedelenlioglu , Ruochen Zeng

In this communication, we introduce a new statistical model and study its various mathematical properties. The expressions for hazard rate, reversed hazard rate, and odd functions are provided. We explore the asymptotic behaviors of the…

Methodology · Statistics 2023-04-24 Tuhin Subhra Mahatao , Subhankar Dutta , Suchandan Kayal

The extremal Fourier intensities are studied for stationary Edwards-Wilkinson-type, Gaussian, interfaces with power-law dispersion. We calculate the probability distribution of the maximal intensity and find that, generically, it does not…

Statistical Mechanics · Physics 2013-05-29 G. Gyorgyi , P. C. W. Holdsworth , B. Portelli , Z. Racz

We study convergence rates of variational posterior distributions for nonparametric and high-dimensional inference. We formulate general conditions on prior, likelihood, and variational class that characterize the convergence rates. Under…

Statistics Theory · Mathematics 2019-06-18 Fengshuo Zhang , Chao Gao

We determine the asymptotic distribution of the sum of correlated variables described by a matrix product ansatz with finite matrices, considering variables with finite variances. In cases when the correlation length is finite, the law of…

Statistical Mechanics · Physics 2014-01-08 Florian Angeletti , Eric Bertin , Patrice Abry

We suggest approximating the distribution of the sum of independent and identically distributed random variables with a Pareto-like tail by combining extreme value approximations for the largest summands with a normal approximation for the…

Probability · Mathematics 2018-02-05 Ulrich K. Mueller

In this paper we discuss the representation of the joint probability density function of perfectly correlated continuous random variables, i.e., with correlation coefficients $\rho=pm1$, by Dirac's $\delta$-function. We also show how this…

Networking and Internet Architecture · Computer Science 2012-05-07 Andrés Alayón Glazunov , Jie Zhang

We introduce new method for generating correlated or uncorrelated Bernoulli random variables by using the binary expansion of a continuous random variable with support on the unit interval. We show that when this variable has a symmetric…

Probability · Mathematics 2023-09-11 Francisco Marcos de Assis , Juliana Martins de Assis , Micael Andrade Dias

We present some new and explicit error bounds for the approximation of distributions. The approximation error is quantified by the maximal density ratio of the distribution $Q$ to be approximated and its proxy $P$. This non-symmetric…

Statistics Theory · Mathematics 2022-09-02 Lutz Duembgen , Richard Samworth , Jon Wellner

Binomial data with unknown sizes often appear in biological and medical sciences and are usually overdispersed. All previous methods used parametric models and only considered overdispersion due to the variation of sizes. The proposed…

Statistics Theory · Mathematics 2007-06-13 Wei Zhang
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