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B0676
Title: Family of matrix-variate distributions: A flexible approach based on the mean-mixture of normal model Authors:  Mehrdad Naderi - University of Pretoria (South Africa) [presenting]
Andriette Bekker - University of Pretoria (South Africa)
Abstract: A new family of matrix-variate distributions is introduced which is based on the mean-mixture of normal (MMN) model. The properties of the new matrix-variate family, namely, stochastic representation, moments and characteristic function, linear and quadratic forms as well as marginal, conditional distributions, are investigated. Three special cases including the restricted skew-normal, exponentiated MMN and the mixed-Weibull MMN matrix variate distributions are presented and studied. Maximum likelihood estimate of the parameters are obtained by implementing an EM-type algorithm. The usefulness and practical utility of the proposed methodology are illustrated through two conducted simulation studies and through the landsat satellite dataset.