On the Gaussian representation of the Riesz probability distribution on symmetric matrices

Abdelhamid Hassairi, Fatma Ktari () and Raoudha Zine
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Abdelhamid Hassairi: Laboratory of Probability and Statistics, Department of Mathematics, Faculty of Sciences of Sfax
Fatma Ktari: Laboratory of Probability and Statistics, Department of Mathematics, Faculty of Sciences of Sfax
Raoudha Zine: Laboratory of Probability and Statistics, Department of Mathematics, Faculty of Sciences of Sfax

AStA Advances in Statistical Analysis, 2022, vol. 106, issue 4, No 4, 609-632

Abstract: Abstract The Riesz probability distribution on symmetric matrices represents an important extension of the Wishart distribution. It is defined by its Laplace transform involving the notion of generalized power. Based on the fact that some Wishart distributions are presented by the mean of the multivariate Gaussian distribution, it is shown that some Riesz probability distributions which are not necessarily Wishart are also presented by the mean of Gaussian samples with missing data. As a corollary, we deduce a Gaussian representation of the inverse Riesz distribution and we give its expectation. The results are assessed in simulation studies.

Keywords: Symmetric matrices; Riesz probability distribution; Inverse Riesz probability distribution; Missing data; Gaussian representation (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10182-022-00436-w

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