UNSPECIFIED (2002) Likelihood inference for location, scale, and shape. JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 108 (1-2). pp. 71-83. ISSN 0378-3758

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Abstract

If (mu, sigma, Sigma) denote the location, scale, and shape parameters of a continuous variate X, we show how the exact likelihood function L(mu, sigma,Sigma\x(1).... x(n)) based on n independent observed values of X can be displayed and used to make frequency-interpretable inferences about any or all of the three parameters. When interest is confined to fewer than three parameters, "simplifying assumptions" may be needed to preserve accuracy in the frequency interpretation. Such simplifying assumptions mathematically resemble Bayesian priors but their logical status is quite different. The approach used leads towards a "Bayes-Frequentist" compromise. (C) 2002 Elsevier Science B.V. All rights reserved.

Item Type:	Journal Article
Subjects:	Q Science > QA Mathematics
Journal or Publication Title:	JOURNAL OF STATISTICAL PLANNING AND INFERENCE
Publisher:	ELSEVIER SCIENCE BV
ISSN:	0378-3758
Date:	1 November 2002
Volume:	108
Number:	1-2
Number of Pages:	13
Page Range:	pp. 71-83
Publication Status:	Published
URI:	http://wrap.warwick.ac.uk/id/eprint/10410

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