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Published online by Cambridge University Press: 01 April 2022
A common view among statisticians is that convergence (which statisticians call consistency) is a necessary property of an inference rule or estimator. In this paper, this view is challenged by appeal to an example in which a rule of inference has a likelihood rationale but is not convergent. The example helps clarify the significance of the likelihood concept in statistical inference.
My thanks to Carter Denniston, A. W. F. Edwards, Ellery Eells, Joe Felsenstein, Isaac Levi, Steven Spielman, and the anonymous referees of this journal for useful discussion and to the National Science Foundation for financial assistance.