非平衡异方差单向分类模型中的广义置信区间

The generalized confidence regions in the one-way classification model of unbalanced heteroscedasticity

讨论了在单向分类模型中多个正态总体样本容量不等,方差不等时样本均值的同时广义置信区间的估计问题.结合Scheffe和Bonferroni区间的定义,给出了相应的广义检验变量及广义枢轴量,进而求得样本均值的同时广义置信区间,并且通过数据模拟,和文献[1]中给出的方法比较,本文所给方法具有较好的可行性.

The paper discusses the simultaneous generalized confidence regions of means estimation of multiple normal populations which means and variances are all different. With the definition of Scheffe and Bonferroni intervals, the paper gives the relevant generalized test variable and generalized pivotal quantity and acquires the simultaneous generalized confidence regions of population means, and through the date simulation and compared with the methods given in literature,the method given in this paper is good feasible.