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Criticism of the predictive distribution

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  • Mathias Raschke

Abstract

The predictive distribution is a mixture of the original distribution model and is used for predicting a future observation. Therein, the mixing distribution is the posterior distribution of the distribution parameters in the Bayesian inference. The mixture can also be computed for the frequentist inference because the Bayesian posterior distribution has the same meaning as a frequentist confidence interval. I present arguments against the concept of predictive distribution. Examples illustrate these. The most important argument is that the predictive distribution can depend on the parameterization. An improvement of the theory of the predictive distribution is recommended.

Suggested Citation

  • Mathias Raschke, 2017. "Criticism of the predictive distribution," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(15), pages 7621-7629, August.
    • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:15:p:7621-7629
    DOI: 10.1080/03610926.2016.1157884
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