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Bayesian Analysis for Binomial Models with Generalized Beta Prior Distributions

Author

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  • James J. Chen
  • Melvin R. Novick

Abstract

The Libby-Novick class of three-parameter generalized beta distributions is shown to provide a rich class of prior distributions for the binomial model that removes some of the restrictions of the standard beta class. The posterior distribution defines a new class of four-parameter generalized beta distributions for which numerical posterior analysis is easily done. A numerical example indicates the desirability of using these wider classes of densities for binomial models, particularly in an interactive computing environment.

Suggested Citation

  • James J. Chen & Melvin R. Novick, 1984. "Bayesian Analysis for Binomial Models with Generalized Beta Prior Distributions," Journal of Educational and Behavioral Statistics, , vol. 9(2), pages 163-175, June.
    • Handle: RePEc:sae:jedbes:v:9:y:1984:i:2:p:163-175
    DOI: 10.3102/10769986009002163
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    Cited by:

    1. Emilio Gómez-Déniz & José María Sarabia, 2018. "A Family of Generalised Beta Distributions: Properties and Applications," Annals of Data Science, Springer, vol. 5(3), pages 401-420, September.

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