Estimating the Common Mean of Possibly Different Normal Populations: A Simulation Study
通过模拟实验比较了不同正态总体共同均值的估计方法，发现基于改进MINQU估计的加权最小二乘估计在方差异质性较小时比最大似然估计更有效，且刀切t统计量在置信区间表现良好。
Abstract Relative efficiency of estimators of the common mean of possibly different normal populations N(μ, σ i 2) is investigated empirically. A weighted least squares estimator , with weights based on a modification of minimum norm quadratic unbiased (MINQU) estimators of the σ i 2, is found to be substantially more efficient than the maximum likelihood (ML) estimator of μ when the heterogeneity in the σ i , is small to moderate and the number of sample observations from a population is small. The jackknife t statistic for performed well in regard to both coverage probability and expected length of the confidence interval.