Likelihood inference for location, scale, and shape
UNSPECIFIED. (2002) Likelihood inference for location, scale, and shape. JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 108 (1-2). pp. 71-83. ISSN 0378-3758Full text not available from this repository.
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|
|Date:||1 November 2002|
|Number of Pages:||13|
|Page Range:||pp. 71-83|
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