Improved chi-squared tests for a composite hypothesis

被引:9
|
作者
Kakizawa, Yoshihide [1 ]
机构
[1] Hokkaido Univ, Fac Econ, Kita Ku, Sapporo, Hokkaido 0600809, Japan
关键词
Asymptotic expansion; Bartlett-type adjustment; Chi-squared approximation; Composite hypothesis; Nuisance parameter; BARTLETT-TYPE MODIFICATION; CORRECTED SCORE TESTS; TEST STATISTICS; GENERAL DISTRIBUTIONS; REGRESSION-MODELS; ORTHOGONALITY; EXPANSIONS; PARAMETER; INFERENCE; SAMPLE;
D O I
10.1016/j.jmva.2012.01.008
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
The Bartlett-type adjustment is a higher-order asymptotic method for improving the chi-squared approximation to the null distributions of various test statistics. Though three influential papers were published in 1991-Chandra and Mukerjee (1991) [8], Cordeiro and Ferrari (1991) [12] and Taniguchi (1991) [36] in alphabetical order, the only CF-approach has been frequently applied in the literature during the last two decades, provided that asymptotic expansion for the null distribution of a given test statistic is available. Revisiting the CM/T-approaches developed in the absence of a nuisance parameter, this paper suggests general adjustments for a class of test statistics that includes, in particular, the likelihood ratio, Rao's and Wald's test statistics in the presence of a nuisance parameter. (C) 2012 Elsevier Inc. All rights reserved.
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页码:141 / 161
页数:21
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