Pure Likelihood Methods

Charles A. Rohde
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Charles A. Rohde: Johns Hopkins University, Bloomberg School of Health

Chapter Chapter 17 in Introductory Statistical Inference with the Likelihood Function, 2014, pp 197-209 from Springer

Abstract: Abstract As we have seen in previous chapters use of the likelihood is important in frequentist methods and in Bayesian methods. In this chapter we explore the use of the likelihood function in another context, that of providing a self-contained method of statistical inference. Richard Royall in his book, Statistical Evidence: A Likelihood Paradigm, carefully developed the foundation for this method building on the work of Ian Hacking and Anthony Edwards. Royall lists three questions of interest to statisticians and scientists after having observed some data 1. What do I do? 2. What do I believe? 3. What evidence do I now have?

Keywords: Likelihood Paradigm; Self-contained Method; Weak Statistical Evidence; Neyman-Pearson Approach; Universal Boundary (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-10461-4_17

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DOI: 10.1007/978-3-319-10461-4_17

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