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In the paper, multivariate probability distributions are considered that are representable as scale mixtures of multivariate elliptically contoured stable distributions. It is demonstrated that these distributions form a special subclass of…

Probability · Mathematics 2019-12-05 Victor Korolev , Alexander Zeifman

In this paper, we study stochastic ordering results between two finite mixtures with single and multiple outliers, assuming subpopulations follow general exponentiated location-scale distributions. For single-outlier mixtures, several…

Statistics Theory · Mathematics 2025-11-04 Raju Bhakta , Kaushik Gupta , Ghobad Saadat Kia , Suchandan Kayal

Let ${\bf X}$ and ${\bf X}$ be two $n$-dimensional elliptical random vectors, we establish an identity for $E[f({\bf Y})]-E[f({\bf X})]$, where $f: \Bbb{R}^n \rightarrow \Bbb{R}$ fulfilling some regularity conditions. Using this identity we…

Statistics Theory · Mathematics 2023-06-22 Chuancun Yin

Several matrix variate hypergeometric type distributions are derived. The compound distributions of left-spherical matrix variate elliptical distributions and inverted hypergeometric type distributions with matrix arguments are then…

Statistics Theory · Mathematics 2009-03-18 Jose A. Diaz-Garcia , R. Gutierrez-Jaimez

We provide a general and rigorous proof for the strong consistency of maximum likelihood estimators of the cumulative distribution function of the mixing distribution and structural parameter under finite mixtures of location-scale…

Statistics Theory · Mathematics 2025-07-21 Guanfu Liu , Pengfei Li , Yukun Liu , Xiaolong Pu

We investigate stochastic comparisons between exponential family distributions and their mixtures with respect to the usual stochastic order, the hazard rate order, the reversed hazard rate order, and the likelihood ratio order. A general…

Statistics Theory · Mathematics 2009-10-05 Yaming Yu

A mixture of shifted asymmetric Laplace distributions is introduced and used for clustering and classification. A variant of the EM algorithm is developed for parameter estimation by exploiting the relationship with the general inverse…

Methodology · Statistics 2017-10-09 Brian C. Franczak , Ryan P. Browne , Paul D. McNicholas

We introduce a mixture of generalized hyperbolic distributions as an alternative to the ubiquitous mixture of Gaussian distributions as well as their near relatives of which the mixture of multivariate t and skew-t distributions are…

Methodology · Statistics 2017-10-09 Ryan P. Browne , Paul D. McNicholas

The stochastic comparisons of parallel and series system are worthy of study. In this paper, we present some stochastic comparisons of parallel and series systems having independent components from Gumble distribution with two parameters…

Statistics Theory · Mathematics 2019-05-03 Surojit Biswas , Nitin Gupta

In this work, we establish some stochastic comparison results for multivariate skew-elliptical random vectors. These multivariate stochastic comparisons involve Hessian and increasing-Hessian orderings as well as many of their special…

Statistics Theory · Mathematics 2023-04-19 Chuancun Yin

Spectral embedding is a procedure which can be used to obtain vector representations of the nodes of a graph. This paper proposes a generalisation of the latent position network model known as the random dot product graph, to allow…

Machine Learning · Statistics 2021-11-17 Patrick Rubin-Delanchy , Joshua Cape , Minh Tang , Carey E. Priebe

We consider component-wise equivariant estimation of order restricted location/scale parameters of a general bivariate distribution under quite general conditions on underlying distributions and the loss function. This paper unifies various…

Statistics Theory · Mathematics 2022-07-05 Naresh Garg , Neeraj Misra

Stochastic localization is a pathwise analysis technique originating from convex geometry. This paper explores certain algorithmic aspects of stochastic localization as a computational tool. First, we unify various existing stochastic…

Statistics Theory · Mathematics 2025-05-20 Tom Alberts , Yiming Xu , Qiang Ye

The consistency of the maximum likelihood estimator for mixtures of elliptically-symmetric distributions for estimating its population version is shown, where the underlying distribution $P$ is nonparametric and does not necessarily belong…

Statistics Theory · Mathematics 2024-10-14 Pietro Coretto , Christian Hennig

A generalization of a distribution increases the flexibility particularly in studying of a phenomenon and its properties. Many generalizations of continuous univariate distributions are available in literature. In this study, an…

Applications · Statistics 2024-08-30 Brijesh P. Singh , Sandeep Singh , Utpal Dhar Das

Stochastic linear combinations of some random vectors are studied where the distribution of the random vectors and the joint distribution of their coefficients are Dirichlet. A method is provided for calculating the distribution of these…

Statistics Theory · Mathematics 2016-03-03 Hazhir Homei

Model-based clustering imposes a finite mixture modelling structure on data for clustering. Finite mixture models assume that the population is a convex combination of a finite number of densities, the distribution within each population is…

Methodology · Statistics 2017-10-09 Cristina Tortora , Paul D. McNicholas , Ryan P. Browne

We introduce a new broad and exible class of multivariate elliptically symmetric distributions in- cluding the elliptically symmetric logistic and multivariate normal. Various probabilistic properties of the new distribution are studied,…

Probability · Mathematics 2018-10-26 Chuancun Yin , Xiuyan Sha

In this paper, we establish the stochastic ordering of the Gini indexes for multivariate elliptical risks which generalized the corresponding results for multivariate normal risks. It is shown that several conditions on dispersion matrices…

Risk Management · Quantitative Finance 2026-03-17 Xuehua Yin , Dan Zhu , Chuancun Yin

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
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