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Wide class of elliptically contoured distributions is a popular model of stock returns distribution. However the important question of adequacy of the model is open. There are some results which reject and approve such model. Such results…

Applications · Statistics 2019-07-25 Petr Koldanov

Recently the termed \emph{multimatrix variate distributions} were proposed in \citet{dgcl:24a} as an alternative for univariate and vector variate copulas. The distributions are based on sample probabilistic dependent elliptically countered…

Statistics Theory · Mathematics 2024-08-06 Francisco J. Caro-Lopera , José A. Díaz-García

We present elliptical processes, a family of non-parametric probabilistic models that subsume Gaussian processes and Student's t processes. This generalization includes a range of new heavy-tailed behaviors while retaining computational…

Machine Learning · Computer Science 2023-11-23 Maria Bånkestad , Jens Sjölund , Jalil Taghia , Thomas B. Schöon

A large class of modern probabilistic learning systems assumes symmetric distributions, however, real-world data tend to obey skewed distributions and are thus not always adequately modelled through symmetric distributions. To address this…

Machine Learning · Statistics 2021-03-16 Shengxi Li , Danilo Mandic

The family of multivariate skew-normal distributions has many interesting properties. It is shown here that these hold for a general class of skew-elliptical distributions. For this class, several stochastic representations are established…

Statistics Theory · Mathematics 2023-09-18 Chuancun Yin , Narayanaswamy Balakrishnan

In this article, we propose a new probabilistic model for the distribution of ranks of elliptic curves in families of fixed Selmer rank, and compare the predictions with previous results, and with the databases of curves over the rationals…

Number Theory · Mathematics 2020-04-02 Alvaro Lozano-Robledo

Azzalini & Dalla Valle (1996) have recently discussed the multivariate skew-normal distribution which extends the class of normal distributions by the addition of a shape parameter. The first part of the present paper examines further…

Methodology · Statistics 2009-11-12 Adelchi Azzalini , Antonella Capitanio

This work sets the matrix variate Birnbaum-Saunders theory in the context of singular distributions and elliptical models. The so termed singular matrix variate generalised Birnbaum-Saunders distribution is obtained with respect the…

Statistics Theory · Mathematics 2019-12-23 José A. Díaz-García , Francisco J. Caro-Lopera

Visual insights into a wide variety of statistical methods, for both didactic and data analytic purposes, can often be achieved through geometric diagrams and geometrically based statistical graphs. This paper extols and illustrates the…

Methodology · Statistics 2013-02-21 Michael Friendly , Georges Monette , John Fox

An expanded family of mixtures of multivariate power exponential distributions is introduced. While fitting heavy-tails and skewness has received much attention in the model-based clustering literature recently, we investigate the use of a…

Methodology · Statistics 2015-06-15 Utkarsh J. Dang , Ryan P. Browne , Paul D. McNicholas

In this paper, the multivariate tail covariance (MTCov) for generalized skew-elliptical distributions is considered. Some special cases for this distribution, such as generalized skew-normal, generalized skew student-t, generalized…

Risk Management · Quantitative Finance 2021-03-10 Baishuai Zuo , Chuancun Yin

Meta-analysis is the aggregation of data from multiple studies to find patterns across a broad range relating to a particular subject. It is becoming increasingly useful to apply meta-analysis to summarize these studies being done across…

Methodology · Statistics 2023-10-25 Olivia Xiao , Stacy Wang , Min Chen

This paper develops a smooth test of goodness-of-fit for elliptical distributions. The test is adaptively omnibus, invariant to affine-linear transformations and has a convenient expression that can be broken into components. These…

Statistics Theory · Mathematics 2019-02-12 Gilles R. Ducharme , Pierre Lafaye de Micheaux

In this short note we provide an analytical formula for the conditional covariance matrices of the elliptically distributed random vectors, when the conditioning is based on the values of any linear combination of the marginal random…

Probability · Mathematics 2017-03-06 Piotr Jaworski , Marcin Pitera

Elliptically symmetric distributions are widely used in portfolio modeling, as well as in signal processing applications for modeling impulsive background noises. Of particular interest are algorithms for covariance estimation and subspace…

Statistics Theory · Mathematics 2016-12-01 Christophe Culan , Claude Adnet

Many variables in the social, physical, and biosciences, including neuroscience, are non-normally distributed. To improve the statistical properties of such data, or to allow parametric testing, logarithmic or logit transformations are…

Methodology · Statistics 2018-01-08 Sacha Jennifer van Albada , Peter A. Robinson

We derive the form of the variance-covariance matrix for any affine equivariant matrix-valued statistics when sampling from complex elliptical distributions. We then use this result to derive the variance-covariance matrix of the sample…

Statistics Theory · Mathematics 2021-11-10 Elias Raninen , Esa Ollila , David E. Tyler

A new family of multivariate distributions, which shall be termed multivector variate distributions, based in the family of the multivariate contoured elliptically distribution is proposed. Several particular cases of multivector variate…

Statistics Theory · Mathematics 2018-06-26 Jose. A. Diaz-Garcia , Francisco J. Caro-Lopera , Fredy O. Perez Ramirez

Products between phase-type distributed random variables and any independent, positive and continuous random variable are studied. Their asymptotic properties are established, and an expectation-maximization algorithm for their effective…

Probability · Mathematics 2021-11-25 Hansjoerg Albrecher , Martin Bladt , Mogens Bladt , Jorge Yslas

We introduce a novel family of projected distributions on the circle and the sphere, namely the circular and spherical projected Cauchy distributions, as promising alternatives for modelling circular and spherical data. The circular…

Methodology · Statistics 2024-09-12 Michail Tsagris , Omar Alzeley