Properties and applications of the generalized likelihood as a summary function for prediction problems

Edward J. Bedrick, Joe R. Hill

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The generalized likelihood plays an important role in parametric inference for prediction and empirical Bayesian models. This paper emphasizes the utility of the generalized likelihood as a summarization procedure in general prediction models. Properties of the generalized likelihood when used in this setting, and examples of its use as a data analytic tool are given in a series of numerical examples.

Original languageEnglish (US)
Pages (from-to)593-609
Number of pages17
JournalScandinavian Journal of Statistics
Volume26
Issue number4
DOIs
StatePublished - Dec 1999
Externally publishedYes

Keywords

  • Bayesian prediction
  • Empirical Bayesian model
  • Induction
  • Likelihood
  • Predictive likelihood

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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