Computing the estimator of a parameter vector via a competing Bayes method

Lichun Wang

Mathematics and Computers in Simulation (MATCOM), 2019, vol. 165, issue C, 271-279

Abstract: Bayesian analysis of normally distributed data with unknown mean and unknown variance is complicated. For the normal distribution N(μ,σ2), a linear Bayes procedure is suggested to simultaneously estimate the parameters μ and σ2. Compared with the usual Bayes estimator and the Lindley approximation, the proposed linear Bayes estimator is simple and easy to use, and some numerical examples are presented to verify its accuracies. Also, the superiorities of the linear Bayes estimator over classical estimators are established in terms of mean squared error matrix criterion.

Keywords: Linear Bayes estimator; Gibbs sampling; Lindley approximation; Mean squared error matrix (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:165:y:2019:i:c:p:271-279

DOI: 10.1016/j.matcom.2019.03.011

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