کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10328136 | 681631 | 2005 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A robust testing procedure for the equality of covariance matrices
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نظریه محاسباتی و ریاضیات
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چکیده انگلیسی
In classical statistics the likelihood ratio statistic used in testing hypotheses about covariance matrices does not have a closed form distribution, but asymptotically under strong normality assumptions is a function of the Ï2-distribution. This distributional approximation totally fails if the normality assumption is not completely met. In this paper we will present multivariate robust testing procedures for the scatter matrix Σ using S-estimates. We modify the classical likelihood ratio test (LRT) into a robust LRT by substituting the robust estimates in the formula in place of classical estimates. A nonlinear formula is also suggested to approximate the degrees of freedom for the approximated Wishart distribution proposed for S-estimates of the shape matrix Σ. We present simulation results to compare the validity and the efficiency of the robust likelihood test to the classical likelihood test.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 49, Issue 3, 1 June 2005, Pages 863-874
Journal: Computational Statistics & Data Analysis - Volume 49, Issue 3, 1 June 2005, Pages 863-874
نویسندگان
Shagufta Aslam, David M. Rocke,