Title: On the matrix-variate generalized hyperbolic distribution and its Bayesian applications
Abstract:Abstract In the first part of the paper, we introduce the matrix-variate generalized hyperbolic distribution by mixing the matrix normal distribution with the matrix generalized inverse Gaussian densi...Abstract In the first part of the paper, we introduce the matrix-variate generalized hyperbolic distribution by mixing the matrix normal distribution with the matrix generalized inverse Gaussian density. The p-dimensional generalized hyperbolic distribution of [Barndorff-Nielsen, O. (1978). Hyperbolic distributions and distributions on hyperbolae. Scand. J. Stat., 5, 151–157], the matrix-T distribution and many well-known distributions are shown to be special cases of the new distribution. Some properties of the distribution are also studied. The second part of the paper deals with the application of the distribution in the Bayesian analysis of the normal multivariate linear model. Keywords: Matrix-variate generalized hyperbolic distributionMatrix normal distributionMatrix generalized inverse Gaussian distributionNormal multivariate linear modelPosterior and prediction distributions Acknowledgements The research was supported in part by the Natural Science and Engineering Research Council of Canada. Thanks to the referee and editor for valuable comments.Read More
Publication Year: 2004
Publication Date: 2004-11-24
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
Cited By Count: 13
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot