On a class of multivariate normal selection priors and its applications in Bayesian inference

DOI10.1016/J.JKSS.2010.05.001zbMath1296.62034OpenAlexW1964555823MaRDI QIDQ744592

Hea-Jung Kim

Publication date: 25 September 2014

Published in: Journal of the Korean Statistical Society (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jkss.2010.05.001

zbMATH Keywords

Gibbs samplerconjugate priorinequality constraintsBayesian hierarchical modelmultivariate normal selection distribution

Mathematics Subject Classification ID

Bayesian inference (62F15) Exact distribution theory in statistics (62E15)

Related Items (4)

On Bayesian estimation of regression models subject to uncertainty about functional constraints ⋮ A measure of uncertainty regarding the interval constraint of normal mean elicited by two stages of a prior hierarchy ⋮ Bayesian variable selection approach to a Bernstein polynomial regression model with stochastic constraints ⋮ A hierarchical Bayesian regression model for the uncertain functional constraint using screened scale mixtures of Gaussian distributions

Uses Software

• BaM

Cites Work

• Conjugate priors for exponential families
• The nontruncated marginal of a truncated bivariate normal distribution
• A Bayesian interpretation of the multivariate skew-normal distribution.
• Randomization Analysis of the Completely Randomized Design Extended to Growth and Response Curves
• Bayes estimation subject to uncertainty about parameter constraints
• The multivariate skew-normal distribution
• A New Skewed Link Model for Dichotomous Quantal Response Data
• A unified view on skewed distributions arising from selections
• On a class of two-piece skew-normal distributions
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