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How Likelihood and Identification went Bayesian

2002/04/01 by John Aldrich · 1 citation
Mathematics · Arts and Humanities · #Probability and Statistical Research #Philosophy and History of Science #Statistics Education and Methodologies #Identification (biology) #Bayesian probability #Maximum likelihood #Bayes factor #Econometrics #Marginal likelihood #Likelihood function #Bayes' theorem #Statistics #Computer science #Mathematics #Artificial intelligence

paper · pdf · doi:10.1111/j.1751-5823.2002.tb00350.x

openalex publication_date 2002/04/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/08

Abstract

Summary This paper considers how the concepts of likelihood and identification became part of Bayesian theory. This makes a nice study in the development of concepts in statistical theory. Likelihood slipped in easily but there was a protracted debate about how identification should be treated. Initially there was no agreement on whether identification involved the prior, the likelihood or the posterior.

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