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On the Invariance, Coincidence, and Statistical Equivalence of the GLRT, Rao Test, and Wald Test

机译:关于GLRT,Rao检验和Wald检验的不变性,重合性和统计等价性

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摘要

Three common techniques to discriminate between alternatives in a binary hypothesis testing problem are: the generalized likelihood ratio test (GLRT), the Rao test, and the Wald test. In this paper, we investigate some characteristics of the corresponding decision statistics and provide their expressions for some problems of particular interest in statistical signal processing. First of all, we focus on the invariance of the Rao and Wald tests with respect to transformations leaving the testing problem unaltered. Then, we introduce necessary and sufficient conditions in order for their decision statistics to coincide with twice the logarithm of the GLRT statistic. Finally, we present some detection problems, usually encountered in practical signal processing applications, where the decision variables of the three quoted tests are equivalent, namely related by strictly monotonic transformations.
机译:在二元假设检验问题中区分替代方案的三种常用技术是:广义似然比检验(GLRT),Rao检验和Wald检验。在本文中,我们研究了相应决策统计的一些特征,并针对统计信号处理中特别关注的一些问题提供了它们的表达。首先,我们关注于Rao和Wald检验关于变换的不变性,从而使检验问题保持不变。然后,我们引入了必要和充分的条件,以便其决策统计与GLRT统计的对数的两倍重合。最后,我们提出了一些实际在信号处理应用中经常遇到的检测问题,其中引用的三个测试的决策变量是等效的,即与严格单调变换有关。

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