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A New Generalized Likelihood Ratio Formula
IEEE Transactions on Systems, Man, and Cybernetics, 1974A new philosophy for designing detection devices, which embodies some of the better features of the classical generalized likelihood ratio test and the classical Bayes test, is presented. A feature of the new Bayes generalized likelihood ratio test is that it provides a unified procedure for utilizing parameter estimates in detector design.
Charles P. Hatsell, Loren W. Nolte
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Expansions of the likelihood ratio and applications
IEEE Transactions on Acoustics, Speech, and Signal Processing, 1986The likelihood ratio receiver, although optimal, is oftentimes difficult to realize. To overcome this difficulty, suboptimal approximations have been studied in the past. One of the simplest approaches is to expand the likelihood ratio and truncate this expansion under the weak signal assumption.
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On the Corrections to the Likelihood Ratio Statistics
Biometrika, 1987Asymptotic expansions of the distributions of likelihood ratio statistics for testing composite null hypotheses against composite alternative hypotheses have been given by \textit{T. Hayakawa} [Ann. Inst. Stat. Math. 29, 359-378 (1977; Zbl 0438.62015)] and \textit{D. N. Lawly} [Biometrika 43, 295-303 (1956; Zbl 0073.136)].
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The Expectation of the Likelihood Ratio Criterion
International Statistical Review / Revue Internationale de Statistique, 1987Quite generally, the likelihood ratio statistic is approximately distributed as a chi-squared statistic. This approximation can be improved by means of a scaling factor. A general formula for approximating this factor is known, but is complicated by the fact that the individual terms of the formula are expressed in a parameter- dependent form.
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