Pure Likelihood Methods and Nuisance Parameters

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

Chapter Chapter 18 in Introductory Statistical Inference with the Likelihood Function, 2014, pp 211-235 from Springer

Abstract: Abstract In most, if not all, statistical problems we have not one parameter but many. However, we are often interested in inference or statements on just one of the parameters. Suppose then that the parameter of interest is θ and that the remaining parameters, called nuisance parameters, are denoted by γ.

Keywords: Called Nuisance Parameters; Profile Likelihood; Orthogonal Similitude; True Likelihood; Conditional Likelihood (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_18

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DOI: 10.1007/978-3-319-10461-4_18

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