Bias correction for T2 type statistic with two-step monotone missing data

被引：4

作者：

Kawasaki, Tamae ^{[1
]}

Seo, Takashi ^{[2
]}

机构：

[1] Tokyo Univ Sci, Grad Sch Sci, Dept Math Informat Sci, Tokyo 162, Japan

[2] Tokyo Univ Sci, Fac Sci, Dept Math Informat Sci, Tokyo 162, Japan

来源：

STATISTICS | 2016年 / 50卷 / 01期

关键词：

asymptotic expansion; Bartlett correction; bias correction; chi-square approximation; modified Bartlett correction; Monte Carlo simulation; stochastic expansion; two-step monotone missing data; MULTIVARIATE NORMAL-DISTRIBUTION; MAXIMUM-LIKELIHOOD-ESTIMATION; TESTING EQUALITY; MEAN VECTORS; SAMPLE; INFERENCE;

D O I：

10.1080/02331888.2015.1060238

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this paper, we consider the problem of testing for the mean vector when the data have a two-step monotone missing pattern. We derive the stochastic expansion of Hotelling's type statistic for the case where the sample size is large. The asymptotic first two moments are obtained using stochastic expansion. We also propose the Bartlett and modified Bartlett corrected statistics for two-step monotone missing data. Finally, we present a numerical comparison based on Monte Carlo simulation for some selected parameters.

引用

页码：76 / 88

页数：13

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