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Statistical Papers

, Volume 60, Issue 1, pp 147–172 | Cite as

Objective Bayesian testing for the linear combinations of normal means

  • Woo Dong Lee
  • Sang Gil Kang
  • Yongku KimEmail author
Regular Article
  • 44 Downloads

Abstract

This study considers objective Bayesian testing for the linear combinations of the means of several normal populations. We propose solutions based on a Bayesian model selection procedure to this problem in which no subjective input is considered. We first construct suitable priors to test the linear combinations of means based on measuring the divergence between competing models (so-called divergence-based priors). Next, we derive the intrinsic priors for which the Bayes factors and model selection probabilities are well defined. Finally, the behavior of the Bayes factors based on the DB priors, intrinsic priors, and classical test are compared in a simulation study and an example.

Keywords

Bayes factor Divergence-based prior Intrinsic prior Linear combinations of normal means Reference prior 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of Data ManagementDaegu Haany UniversityKyungsanKorea
  2. 2.Department of Computer and Data InformationSangji UniversityWonjuKorea
  3. 3.Department of StatisticsKyungpook National UniversityDaeguKorea

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