Journal of the Korean Statistical Society
- Volume 28 Issue 1
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- Pages.107-124
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- 1999
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- 1226-3192(pISSN)
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- 2005-2863(eISSN)
A Bayesian Test Criterion for the Multivariate Behrens-Fisher Problem
Abstract
An approximate Bayes criterion for multivariate Behrens-Fisher problem is proposed and examined. Development of the criterion involves derivation of approximate Bayes factor using the imaginary training sample approach introduced by Speigelhalter and Smith (1982). The criterion is designed to develop a Bayesian test, so that it provides an alternative test to other tests based upon asymptotic sampling theory (such as the tests suggested by Bennett(1951), James(1954) and Yao(1965). For the derived criterion, numerical studies demonstrate routine application and give comparisons with the classical tests.
Keywords
- Multivariate Behrens-Fisher problem;
- Bayes test criterion;
- Default Bayes factor;
- Improper prior;
- Imaginary training sample method;
- Classical test criteria;
- p-vaule