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Probability matching priors for predicting unobservable random effects with application to ANOVA models

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  • Chang, In Hong
  • Kim, Byung Hwee
  • Mukerjee, Rahul

Abstract

We characterize priors that ensure approximate frequentist validity of posterior quantiles of unobservable random effects. Application to analysis of variance (ANOVA) models is explored.

Suggested Citation

  • Chang, In Hong & Kim, Byung Hwee & Mukerjee, Rahul, 2003. "Probability matching priors for predicting unobservable random effects with application to ANOVA models," Statistics & Probability Letters, Elsevier, vol. 62(3), pages 223-228, April.
    • Handle: RePEc:eee:stapro:v:62:y:2003:i:3:p:223-228
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    References listed on IDEAS

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    1. J. Ghosh & Rahul Mukerjee, 1993. "Frequentist validity of highest posterior density regions in the multiparameter case," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 45(2), pages 293-302, June.
    2. Gauri Datta & Rahul Mukerjee, 2003. "Probability matching priors for predicting a dependent variable with application to regression models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 55(1), pages 1-6, March.
    3. J. Ghosh & Rahul Mukerjee, 1993. "Corrections to “Frequentist validity of highest posterior density regions in the multiparameter case”," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 45(3), pages 602-602, September.
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