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Journal of Statistical Theory and Practice

, Volume 5, Issue 4, pp 675–682 | Cite as

When Population Size Does Not Matter: Robust Bayesian Testing for Categorical Populations

  • Sudip Bose
  • Mark Bauder
Article

Abstract

We present a strongly robust Bayesian test of the hypothesis of equality of distributions for populations consisting of data in finitely many categories. The Bayes factors are the same for infinite and finite populations. Under the hypothesis of inequality, one distribution can be viewed as an exponentially tilted or exponentially distorted version of another. We illustrate the method by calculating Bayes factors for a range of data values.

AMS Subject Classification. Primary

62F15 62F03 62F35 Secondary 62E15 

Key-words

Tests of hypotheses Multiple populations SRSWOR Finite population sampling Bayes-ian testing Bayes factor Bayesian robustness Robust testing Limit distribution Exponential tilting Exponential distortion 

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Copyright information

© Grace Scientific Publishing 2011

Authors and Affiliations

  1. 1.Department of StatisticsThe George Washington UniversityWashington, D.C.USA

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