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Activity Number: 427 - SPEED: Bayesian Methods, Part 2
Type: Contributed
Date/Time: Tuesday, July 30, 2019 : 3:05 PM to 3:50 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #307871
Title: Predictive Density Estimation of Multivariate Skew-Normal Distribution
Author(s): Othmane Kortbi*
Companies: UAE University Al-Ain
Keywords: Predictive density; Skew-normal distribution; KullbackÔÇôLeibler loss; Bayes estimator; Minimum risk equivariant; Dominance

This work studies decision theoretic properties of predictive density estimators for multivariate skew-normal distribution with known skewness parameters under Kullback-Leibler loss. We investigated the properties of the benchmark estimator which is the the minimum risk equivariant predictive density estimator. A wide class of plug-in estimators improving on the best equivariant estimator is constructed when the dimension of the location parameters is larger than or equal to four. A class of Bayes estimators is also considered and their dominance property studied. The performances of these estimators are investigated by simulation.

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