Interval Estimation Based on the Profile Likelihood: Strong Lagrangian Theory with Applications to Discrimination
本文利用强拉格朗日理论简化了剖面对数似然的计算，并应用于两总体判别问题中后验对数优势比的区间估计，特别处理了多元正态不等协方差矩阵情形。
Strong Lagrangian theory is used to illuminate the properties of the profile log likelihood. General conditions are given which lead to a simplification of the computations required to plot this function or calculate interval estimates based upon it. The results presented are rather general with a variety of possible applications. In particular, it is shown that they provide a simple solution to the important practical problem of obtaining an interval estimate for the posterior log odds ratio in the two population discrimination problem. The results are applied to the multivariate normal unequal covariance matrix case and are illustrated by an application.