双向分类随机效应套模型中异常值的UMPU检验
UMPU Test of Outliers in Random-effects Model of Two-way Nested Classification
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摘要: 本文就平衡的(Balanced)双向分类随机效应套模型,讨论了主效应均值滑动模型的异常值检验问题,并给出了似然比检验统计量.在零假设及备择假设下导出了检验统计量的分布,证明了检验的一致最优无编(UMPU)性.最后对相关问题进行了讨论。Abstract: In this paper, we study outlier testing problem under the mean-shift model of main effects in balanced two-way nested classification. The likelihood ratio statistic is derived,and its distribution under the null and alternative hypothesis are obtained respectiverly. A property of uniformly most powerful unbiasedness (UMPU) is proved. Finally some related topics are discussed.