کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
417414 | 681501 | 2016 | 8 صفحه PDF | دانلود رایگان |
Large covariance matrices play a fundamental role in various high-dimensional statistics. Investigating the limiting behavior of the eigenvalues can reveal informative structures of large covariance matrices, which is particularly important in high-dimensional principal component analysis and covariance matrix estimation. In this paper, we propose a framework to test the number of distinct population eigenvalues for large covariance matrices, i.e. the order of a Population Spectral Distribution. The limiting distribution of our test statistic for a Population Spectral Distribution of order 2 is developed along with its (N,p)(N,p) consistency, which is clearly demonstrated in our simulation study. We also apply our test to two classical microarray datasets.
Journal: Computational Statistics & Data Analysis - Volume 95, March 2016, Pages 75–82