Linear Bayesian estimators for linear models with constraints. Issue 8 (24th May 2021)

• Record Type: Journal Article
• Authors: Zhang, Fengyue; Wang, Lichun
• Is Part Of: Journal of statistical computation and simulation. Volume 91:Issue 8(2021)
• Page Start: 1635
• Page End: 1650
• Publication Date: 2021-05-24
• Subjects: Equality constraints -- linear Bayesian estimator -- Gibbs sampling -- Lindley approximation; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5028505
• DOI: 10.1080/00949655.2020.1864732
• Languages: English
• ISSNs: 0094-9655

Abstract

Abstract : The paper employs a linear Bayesian procedure to simultaneously estimate regression parameters and variance parameter in a linear model with equality constraints. We obtain the expression of the linear Bayesian estimator (LBE) for the parameter vector, which consists of the regression parameters and the variance parameter, without specifying the specific form of the prior. The superiorities of the proposed LBE over some classical estimators are established in terms of mean squared error matrix criterion. Monte Carlo simulations and a numerical example are presented to compare its performances with those of the usual Bayesian estimator and the Lindley approximation as well.