Asymptotic expansion of the null distribution of LR statistic for multivariate linear hypothesis when the dimension is large

被引:16
|
作者
Tonda, T
Fujikoshi, Y
机构
[1] Hiroshima Univ, Grad Sch Sci, Dept Math, Higashihiroshima 7398526, Japan
[2] Hiroshima Univ, Res Inst Radiat Biol & Med, Dept Environmetr & Biometr, Hiroshima, Japan
关键词
asymptotic expansion; high-dimensional case; likelihood ratio statistic; multivariate linear hypothesis;
D O I
10.1081/STA-120029835
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 derive an asymptotic expansion of the null distribution of likelihood ratio statistic for multivariate linear hypothesis when the dimension is comparable to the sample size. Our asymptotic approximations are numerically compared with some other approximations including the large sample approximation due to Box [Box, G. E. P. (1949). A general distribution theory for a class of likelihood criteria. Biometrika 36:317-346]. It is shown that the approximations proposed in this paper are good when the dimension is large and close to the sample size, and further our approximations are similar to the Box's approximation even for most of the usual large sample cases.
引用
收藏
页码:1205 / 1220
页数:16
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