Likelihood and Convergence
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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.
[1] A. Wald. Note on the Consistency of the Maximum Likelihood Estimate , 1949 .
[2] P. Whittle,et al. Lectures and conferences on mathematical statistics and probability , 1952 .
[3] G. A. Barnard,et al. THE LOGIC OF STATISTICAL INFERENCE1 , 1972, The British Journal for the Philosophy of Science.
[4] M. Kendall,et al. The advanced theory of statistics , 1945 .
[5] H. Jeffreys. MAXIMUM LIKELIHOOD, INVERSE PROBABILITY AND THE METHOD OF MOMENTS , 1938 .