Title : ( Wishart distributions: Advances in theory with Bayesian application )
Authors: Andriette Bekker , Janetvan Niekerk , Mohammad Arashi ,
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Abstract
In this paper, we generalize the Wishart distribution utilizing a fresh approach that leads to the hypergeometric Wishart generator distribution with the Wishart generator and the Wishart as special cases. Important statistical characteristics are derived. The significance of this generator distribution is further demonstrated by assuming a special case as a prior for the underlying matrix variate normal model.
Keywords
, Bayesian estimation, Frobenius norm, Hypergeometric Wishart, Matrix-variate convergence, Matrix-variate normal, Wishart distribution
@article{paperid:1081575,
author = {Andriette Bekker and Janetvan Niekerk and Arashi, Mohammad},
title = {Wishart distributions: Advances in theory with Bayesian application},
journal = {Journal of Multivariate Analysis},
year = {2017},
volume = {155},
month = {March},
issn = {0047-259X},
pages = {272--283},
numpages = {11},
keywords = {Bayesian estimation; Frobenius norm; Hypergeometric Wishart; Matrix-variate convergence; Matrix-variate normal; Wishart distribution},
}
%0 Journal Article
%T Wishart distributions: Advances in theory with Bayesian application
%A Andriette Bekker
%A Janetvan Niekerk
%A Arashi, Mohammad
%J Journal of Multivariate Analysis
%@ 0047-259X
%D 2017
