The Annals of Mathematical Statistics

The Weighted Likelihood Ratio, Linear Hypotheses on Normal Location Parameters

James M. Dickey

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Abstract

Raiffa and Schlaifer's theory of conjugate prior distributions is here applied to Jeffrey's theory of tests for a sharp hypothesis, for simple normal sampling, for model I analysis of variance, and for univariate and multivariate Behrens-Fisher probelms. Leonard J. Savage's Bayesianization of Jeffrey's theory is given with new generalizations. A new conjugate prior family for normal sampling which allows prior independence of unknown mena and variance is given.

Article information

Source
Ann. Math. Statist., Volume 42, Number 1 (1971), 204-223.

Dates
First available in Project Euclid: 27 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aoms/1177693507

Digital Object Identifier
doi:10.1214/aoms/1177693507

Mathematical Reviews number (MathSciNet)
MR309225

Zentralblatt MATH identifier
0274.62020

JSTOR
links.jstor.org

Citation

Dickey, James M. The Weighted Likelihood Ratio, Linear Hypotheses on Normal Location Parameters. Ann. Math. Statist. 42 (1971), no. 1, 204--223. doi:10.1214/aoms/1177693507. https://projecteuclid.org/euclid.aoms/1177693507


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