Abstract:Inference about a scalar parameter of interest typically relies on the asymptotic normality of common likelihood pivots, such as the signed likelihood root, the score and Wald statistics. Nevertheless, the resulting inferential procedures have been known to perform poorly when the dimension of the nuisance parameter is large relative to the sample size and when the information about the parameters is limited. In such cases, the use of asymptotic normality of analytical modifications of the signed likelihood ro… Show more
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