Posterior odds ratios for selected regression hypotheses

Trabajos de Estadistica Y de Investigacion Operativa volume 31, pages585–603(1980)Cite this article

Summary

Bayesian posterior odds ratios for frequently encountered hypotheses about parameters of the normal linear multiple regression model are derived and discussed. For the particular prior distributions utilized, it is found that the posterior odds ratios can be well approximated by functions that are monotonic in usual sampling theoryF statistics. Some implications of this finding and the relation of our work to the pioneering work of Jeffreys and others are considered. Tabulations of odds ratios are provided and discussed.

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Affiliations

  1. University of Chicago, Chicago, USA

    A. Zellner & A. Siow

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  1. A. Zellner
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  2. A. Siow
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Correspondence to A. Zellner.

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Zellner, A., Siow, A. Posterior odds ratios for selected regression hypotheses. Trabajos de Estadistica Y de Investigacion Operativa 31, 585–603 (1980). https://doi.org/10.1007/BF02888369

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Keywords

  • Bayesian Odds Ratios
  • Hypothesis Testing
  • Regression Hypotheses
  • Regression Model