Journal article
Bayesian inference for the precision matrix for scale mixtures of normal distributions
Communications in Statistics - Theory and Methods, Vol.41(24), pp.4407-4412
2012
Abstract
Baysian inference is considered for the precision matrix of the multivariate regression model with distribution of the random responses belonging to the multivariate scale mixtures of normal distributions. The posterior distribution and some identities involving expectations taken with respect to this posterior distribution are derived when the prior distribution of the parameters is from the conjugate family. The results are specialized to the case where the random responses have a matrix-t distribution and thus generalizing the results of Zellner (1976) and Muirhead (1986).
Details
- Title
- Bayesian inference for the precision matrix for scale mixtures of normal distributions
- Authors/Creators
- V.M. Ng (Author/Creator)
- Publication Details
- Communications in Statistics - Theory and Methods, Vol.41(24), pp.4407-4412
- Publisher
- Marcel Dekker Inc.
- Identifiers
- 991005545322007891
- Copyright
- © Taylor & Francis Group, LLC
- Murdoch Affiliation
- School of Chemical and Mathematical Science
- Language
- English
- Resource Type
- Journal article
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- Citation topics
- 9 Mathematics
- 9.92 Statistical Methods
- 9.92.220 Robust Estimation
- Web Of Science research areas
- Statistics & Probability
- ESI research areas
- Mathematics