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基于一类 M 估计量的简便精确单侧推断AI 解读

This paper presents a simple method of calculating one-sided p-values which yield accurate inferences for a simple null hypothesis or, equivalently, accurate one-sided confidence limits regarding a scalar parameter in the presence of nuisance parameters. The method, which extends the work of DiCiccio et al. (2001) and Lee & Young (2005) in the context of adjusted likelihood estimation, is based on a test statistic analogous to the signed root of the loglikelihood, but…

多维目标参数情形下剖面似然的二阶调整AI 解读

Summary Inference in the presence of nuisance parameters is often carried out by using the χ2-approximation to the profile likelihood ratio statistic. However, in small samples, the accuracy of such procedures may be poor, in part because the profile likelihood does not behave as a true likelihood, in particular having a profile score bias and information bias which do not vanish. To account better for nuisance parameters, various researchers have suggested that inference be…

近似贝叶斯推断的 Bartlett 调整AI 解读

In wide generality, the posterior distributions of the likehood ratio statistic and the posterior ratio statistic are chi-squared to error of order O(n−1), where n is sample size. The error in the chi-squared approximation can be reduced to order O(n−2) by Bartlett correction. In this paper, explicit formulae are derived for the Bartlett adjustment factors of both statistics, and the derivations are based on the Tierney. Kass & Kadane (1989) asymptotic approximation for…

近似贝叶斯推断中的 Bartlett 调整AI 解读

In wide generality, the posterior distributions of the likehood ratio statistic and the posterior ratio statistic are chi-squared to error of order O(n−1), where n is sample size. The error in the chi-squared approximation can be reduced to order O(n−2) by Bartlett correction. In this paper, explicit formulae are derived for the Bartlett adjustment factors of both statistics, and the derivations are based on the Tierney. Kass & Kadane (1989) asymptotic approximation for…