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Main Authors: Yadav, Pooja, Srivastava, Tanuja
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2502.04118
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author Yadav, Pooja
Srivastava, Tanuja
author_facet Yadav, Pooja
Srivastava, Tanuja
contents This paper considers an extension of the multivariate symmetric Laplace distribution to matrix variate case. The symmetric Laplace distribution is a scale mixture of normal distribution. The maximum likelihood estimators (MLE) of the parameters of multivariate and matrix variate symmetric Laplace distribution are proposed, which are not explicitly obtainable, as the density function involves the modified Bessel function of the third kind. Thus, the EM algorithm is applied to find the maximum likelihood estimators. The parameters and their maximum likelihood estimators of matrix variate symmetric Laplace distribution are defined up to a positive multiplicative constant with their Kronecker product uniquely defined. The condition for the existence of the MLE is given, and the stability of the estimators is discussed. The empirical bias and the dispersion of the Kronecker product of the estimators for different sample sizes are discussed using simulated data.
format Preprint
id arxiv_https___arxiv_org_abs_2502_04118
institution arXiv
publishDate 2025
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spellingShingle Maximum Likelihood Estimation of the Parameters of Matrix Variate Symmetric Laplace Distribution
Yadav, Pooja
Srivastava, Tanuja
Statistics Theory
This paper considers an extension of the multivariate symmetric Laplace distribution to matrix variate case. The symmetric Laplace distribution is a scale mixture of normal distribution. The maximum likelihood estimators (MLE) of the parameters of multivariate and matrix variate symmetric Laplace distribution are proposed, which are not explicitly obtainable, as the density function involves the modified Bessel function of the third kind. Thus, the EM algorithm is applied to find the maximum likelihood estimators. The parameters and their maximum likelihood estimators of matrix variate symmetric Laplace distribution are defined up to a positive multiplicative constant with their Kronecker product uniquely defined. The condition for the existence of the MLE is given, and the stability of the estimators is discussed. The empirical bias and the dispersion of the Kronecker product of the estimators for different sample sizes are discussed using simulated data.
title Maximum Likelihood Estimation of the Parameters of Matrix Variate Symmetric Laplace Distribution
topic Statistics Theory
url https://arxiv.org/abs/2502.04118