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Bayesian Model Choice: Asymptotics and Exact Calculations
Abstract : Model determination is a fundamental data analytic task. Here we consider the problem of choosing amongst a finite (with loss of generality we assume two) set of models. After brieflyExpand
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A Bayesian approach to inferring population structure from dominant markers
Molecular markers derived from polymerase chain reaction (PCR) amplification of genomic DNA are an important part of the toolkit of evolutionary geneticists. Random amplified polymorphic DNA markersExpand
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A new class of multivariate skew distributions with applications to Bayesian regression models
The authors develop a new class of distributions by introducing skewness in multivariate ellip- tically symmetric distributions. The class, which is obtained by using transformation and conditioning,Expand
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Model Determination Using Predictive Distributions with Implementation via Sampling-Based Methods
Abstract : Model determination is divided into the issues of model adequacy and model selection. Predictive distributions are used to address both issues. This seems natural since, typically,Expand
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A General Class of Multivariate Skew-Elliptical Distributions
This paper proposes a general class of multivariate skew-elliptical distributions. We extend earlier results on the so-called multivariate skew-normal distribution. This family of distributionsExpand
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Estimation of a covariance matrix under Stein's loss
On decrit la technique generale de Stein pour ameliorer l'estimateur sans biais invariant le meilleur et l'estimateur minimax de la matrice de covariance normale
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Skewed multivariate models related to hidden truncation and/or selective reporting
The univariate skew-normal distribution was introduced by Azzalini in 1985 as a natural extension of the classical normal density to accommodate asymmetry. He extensively studied the properties ofExpand
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A first course in linear model theory
A Review of Vector and Matrix Algebra. Properties of Special Matrices. Generalized Inverse and Solutions to Linear Systems. The General Linear Model. Multivariate Normal And Related Distributions.Expand
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Bayesian analysis of outlier problems using divergence measures
A Bayesian approach is presented for detecting influential observations using general divergence measures on the posterior distributions. A sampling-based approach using a Gibbs orExpand
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A New Skewed Link Model for Dichotomous Quantal Response Data
Abstract The logit, probit, and student t-links are widely used in modeling dichotomous quantal response data. Most of the commonly used link functions are symmetric, except the complementary log-logExpand
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