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Objective Bayes, conditional inference and the signed root likelihood ratio statistic

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  • Thomas J. Diciccio
  • Todd A. Kuffner
  • G. Alastair Young

Abstract

Bayesian properties of the signed root likelihood ratio statistic are analysed. Conditions for first-order probability matching are derived by the examination of the Bayesian posterior and frequentist means of this statistic. Second-order matching conditions are shown to arise from matching of the Bayesian posterior and frequentist variances of a mean-adjusted version of the signed root statistic. Conditions for conditional probability matching in ancillary statistic models are derived and discussed. Copyright 2012, Oxford University Press.

Suggested Citation

  • Thomas J. Diciccio & Todd A. Kuffner & G. Alastair Young, 2012. "Objective Bayes, conditional inference and the signed root likelihood ratio statistic," Biometrika, Biometrika Trust, vol. 99(3), pages 675-686.
    • Handle: RePEc:oup:biomet:v:99:y:2012:i:3:p:675-686
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    File URL: http://hdl.handle.net/10.1093/biomet/ass028
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    Cited by:

    1. Thomas J. DiCiccio & Todd A. Kuffner & G. Alastair Young, 2017. "A Simple Analysis of the Exact Probability Matching Prior in the Location-Scale Model," The American Statistician, Taylor & Francis Journals, vol. 71(4), pages 302-304, October.

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