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How Likelihood and Identification went Bayesian
Author(s) -
Aldrich John
Publication year - 2002
Publication title -
international statistical review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.051
H-Index - 54
eISSN - 1751-5823
pISSN - 0306-7734
DOI - 10.1111/j.1751-5823.2002.tb00350.x
Subject(s) - identification (biology) , bayesian probability , maximum likelihood , bayes factor , econometrics , marginal likelihood , likelihood function , bayes' theorem , statistics , computer science , mathematics , artificial intelligence , botany , biology
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.