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The objective of the paper is to study accuracy of multi-class classification in high-dimensional setting, where the number of classes is also large ("large $L$, large $p$, small $n$" model). While this problem arises in many practical…

Statistics Theory · Mathematics 2019-07-18 Felix Abramovich , Marianna Pensky

Mixtures of regression are a powerful class of models for regression learning with respect to a highly uncertain and heterogeneous response variable of interest. In addition to being a rich predictive model for the response given some…

Statistics Theory · Mathematics 2024-01-30 Dat Do , Linh Do , XuanLong Nguyen

This paper introduces some new characterizations of COM-Poisson random variables. First, it extends Moran-Chatterji characterization and generalizes Rao-Rubin characterization of Poisson distribution to COM-Poisson distribution. Then, it…

Probability · Mathematics 2018-09-26 Bo Li , Huiming Zhang , Jiao He

This article considers exponential families of truncated multivariate normal distributions with one-sided truncation for some or all coordinates. We observe that if all components are one-sided truncated then this family is not full. The…

Statistics Theory · Mathematics 2025-07-02 Michael Levine , Donald Richards , Jianxi Su

The unified skew-t (SUT) is a flexible parametric multivariate distribution that accounts for skewness and heavy tails in the data. A few of its properties can be found scattered in the literature or in a parameterization that does not…

Methodology · Statistics 2023-12-01 Kesen Wang , Maicon J. Karling , Reinaldo B. Arellano-Valle , Marc G. Genton

This paper conducts sensitivity analysis of random constraint and variational systems related to stochastic optimization and variational inequalities. We establish efficient conditions for well-posedness, in the sense of robust Lipschitzian…

Optimization and Control · Mathematics 2021-12-13 Boris S. Mordukhovich , Pedro Pérez-Aros

We consider a Bayesian approach to variable selection in the presence of high dimensional covariates based on a hierarchical model that places prior distributions on the regression coefficients as well as on the model space. We adopt the…

Statistics Theory · Mathematics 2014-07-28 Naveen Naidu Narisetty , Xuming He

The purpose of this paper is to establish a general strong law of large numbers (SLLN) for arbitrary sequences of random variables (rv's) based on the squared indice method and to provide applications to SLLN of associated sequences. This…

Probability · Mathematics 2015-06-30 Harouna Sangare , Gane Samb Lo

In this work, we consider a multivariate regression model with one-sided errors. We assume for the regression function to lie in a general H\"{o}lder class and estimate it via a nonparametric local polynomial approach that consists of…

Statistics Theory · Mathematics 2021-02-11 Leonie Selk , Charles Tillier , Orlando Marigliano

The regular variation model for multivariate extremes decomposes the joint distribution of the extremes in polar coordinates in terms of the angles and the norm of the random vector as the product of two independent densities: the angular…

Methodology · Statistics 2025-08-08 Fernández-Durán , J. J. , Gregorio-Domínguez , M. M

The broad class of multivariate unified skew-normal (SUN) distributions has been recently shown to possess important conjugacy properties. When used as priors for the coefficients vector in probit, tobit, and multinomial probit models,…

Methodology · Statistics 2024-08-06 Maicon J. Karling , Daniele Durante , Marc G. Genton

The tail behavior of aggregates of heavy-tailed random vectors is known to be determined by the so-called principle of "one large jump'', be it for finite sums, random sums, or, L\'evy processes. We establish that, in fact, a more general…

Probability · Mathematics 2023-01-26 Bikramjit Das , Vicky Fasen-Hartmann

In recent years, stochastic dominance for independent and identically distributed (iid) infinite-mean random variables has received considerable attention. The literature has identified several classes of distributions of nonnegative random…

Probability · Mathematics 2026-04-28 Keyi Zeng , Zhenfeng Zou , Yuting Su , Taizhong Hu

The article is devoted to the study of exponential statistical structures of type B, which constitute a subclass of exponential families of probability distributions. This class is characterized by a number of analytical and probabilistic…

Statistics Theory · Mathematics 2025-12-23 Oleksandr Volkov , Yurii Volkov

In this paper we generalize Yu's [Ann. Probab. 24 (1996) 2079-2097] strong invariance principle for associated sequences to the multi-parameter case, under the assumption that the covariance coefficient u(n) decays exponentially as n\to…

Probability · Mathematics 2007-05-23 Raluca M. Balan

We prove a general transfer theorem for multivariate random sequences with independent random indexes in the double array limit setting. We also prove its partial inverse providing necessary and sufficient conditions for the convergence of…

Probability · Mathematics 2016-11-04 V. Yu. Korolev , A. I. Zeifman

This paper considers inference for conditional moment inequality models using a multiscale statistic. We derive the asymptotic distribution of this test statistic and use the result to propose feasible critical values that have a simple…

Applications · Statistics 2015-12-10 Timothy B. Armstrong , Hock Peng Chan

We characterize the exponential distribution as the only one which satisfies a regression condition. This condition involves the regression function of a fixed record value given two other record values, one of them being previous and the…

Probability · Mathematics 2011-05-06 George P. Yanev

The problem of sums of independent, identically distributed random variables with stretched-exponential tails exhibits a dynamical phase transition and has recently reemerged in the context of active transport and condensation phenomena. We…

Statistical Mechanics · Physics 2026-05-11 Alberto Bassanoni , Omer Hamdi

We introduce a novel generative formulation of deep probabilistic models implementing "soft" constraints on their function dynamics. In particular, we develop a flexible methodological framework where the modeled functions and derivatives…

Machine Learning · Statistics 2018-06-19 Marco Lorenzi , Maurizio Filippone
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