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This paper proposes a generalisation of the Pearson type II distribution, which shall termed Pearson Type II-Riesz distribution, based in the Kotz-Riesz distribution. Specifically, the central nonsingular matricvariate generalised Pearson…

Statistics Theory · Mathematics 2015-06-17 Jose A. Diaz-Garcia , Francisco J. Caro-Lopera

Supposing Kotz-Riesz type I and II distributions and their corresponding independent univariate Riesz distributions the associated generalised matrix multivariate T distributions, termed matrix multivariate T-Riesz distributions are…

Statistics Theory · Mathematics 2015-06-17 Jose A. Diaz-Garcia , Ramon Gutierrez-Sanchez

This paper proposes a unified approach to enable the study of diverse distributions in the real, complex, quaternion and octonion cases, simultaneously. In particular, the central, nonsingular matricvariate and matrix multivariate Pearson…

Statistics Theory · Mathematics 2010-11-24 Jose A. Diaz-Garcia , Ramon Gutierrez-Jaimez

Assuming Kotz-Riesz type I and II distributions and their corresponding independent Riesz distributions the associated generalised matricvariate T distributions, termed matricvariate T-Riesz distributions for real normed division algebras…

Statistics Theory · Mathematics 2015-06-17 Jose A. Diaz-Garcia , Ramon Gutierrez-Sanchez

In this paper, the study of bivariate generalised beta type I and II distributions is extended to the complex matrix variate case, for which the corresponding density functions are found. In addition, for complex bimatrix variate beta type…

Statistics Theory · Mathematics 2009-06-08 Jose A. Diaz-Garcia , Ramon Gutierrez-Jaimez

In this paper, we extend the study of bivariate generalised beta type I and II distributions to the matrix variate case.

Statistics Theory · Mathematics 2009-04-14 J. A. Diaz-Garcia , R. Gutierrez-Jaimez

This article derives several properties of the Riesz distributions, such as their corresponding Bartlett decompositions, the inverse Riesz distributions and the distribution of the generalised variance for real normed division algebras. In…

Statistics Theory · Mathematics 2015-06-17 José A. Diaz-Garcia

Several distributions are studied, simultaneously in the real, complex, quaternion and octonion cases. Specifically, these are the central, nonsingular matricvariate and matrix multivariate T and beta type II distributions and the joint…

Statistics Theory · Mathematics 2010-11-24 Jose A. Diaz-Garcia , Ramon Gutierrez-Jaimez

The aim of this paper is to study the mixture of the Riesz distribution on symmetric matrices with respect to the multivariate Poisson distribution. We show, in particular, that this distribution is related to the modified Bessel function…

Probability · Mathematics 2009-01-13 Abdelhamid Hassairi , Mahdi Louati

In this paper, the densities of the doubly singular beta type I and II distributions are found, and the joint densities of their corresponding nonzero eigenvalues are provided. As a consequence, the density function of a singular inverted…

Statistics Theory · Mathematics 2009-04-15 J. A. Diaz-Garcia , R. Gutierrez-Jaimez

This article derives the distribution of random matrix $\mathbf{X}$ associated with the transformation $\mathbf{Y} = \mathbf{X}^{*}\mathbf{X}$, such that $\mathbf{Y}$ has a Riesz distribution for real normed division algebras. Two versions…

Statistics Theory · Mathematics 2015-06-17 Jose A. Diaz-Garcia

In this note, we define a Gaussian probability distribution over matrices. We prove some useful properties of this distribution, namely, the fact that marginalization, conditioning, and affine transformations preserve the matrix Gaussian…

Probability · Mathematics 2018-06-22 Shane Barratt

The distribution functions of the matricvariate beta type I and II distributions are studied under real normed division algebras. The unified approach for real, complex, quaternions and octonions, also considers general properties and…

Statistics Theory · Mathematics 2024-09-27 José A. Díaz-García , Francisco J. Caro-Lopera

In this article, we define a matrix multinomial distribution. We prove some properties of the matrix multinomial distribution. We prove that the matrix Poisson distribution can be used as an approximation to the matrix multinomial…

Probability · Mathematics 2021-04-30 Yuriy Yurchenko

We provide a new and simple characterization of the multivariate generalized Laplace distribution. In particular, this result implies that the product of a Gaussian matrix with independent and identically distributed columns by an…

Probability · Mathematics 2017-04-06 Pierre-Alexandre Mattei

The Wishart probability distribution on symmetricmatrices has been initially defined by mean of the multivariateGaussian distribution as an of the chi-square distribution. A moregeneral definition is given using results for harmonic…

Probability · Mathematics 2017-12-19 Abdelhamid Hassairi

In this paper, we determine the density functions of nonsymmetrised doubly noncentral matrix variate beta type I and II distributions. The nonsymetrised density functions of doubly noncentral and noncentral bimatrix variate generalised beta…

Statistics Theory · Mathematics 2009-06-08 Jose A. Diaz-Garcia , Ramon Gutierrez-Jaimez

Motivated by the need, in some Bayesian likelihood free inference problems, of imputing a multivariate counting distribution based on its vector of means and variance-covariance matrix, we define a generic multivariate discrete…

Applications · Statistics 2011-03-28 Marcos Capistrán , J. Andrés Christen

In \cite{Diaz} beta type I and II doubly singular distributions were introduced and their densities and the joint densities of nonzero eigenvalues were derived. In such matrix variate distributions $p$, the dimension of two singular Wishart…

Statistics Theory · Mathematics 2020-01-07 Stepan Grinek

The Wishart distribution and its generalizations are among the most prominent probability distributions in multivariate statistical analysis, arising naturally in applied research and as a basis for theoretical models. In this paper, we…

Statistics Theory · Mathematics 2015-02-26 A. Bekker , M. Arashi , J. van Niekerk
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