Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7546336 | Journal of Multivariate Analysis | 2018 | 35 Pages |
Abstract
Let Sp,1, Sp,2 be two independent pÃp sample covariance matrices with degrees of freedom n1 and n2, respectively, whose corresponding population covariance matrices are Σp,1 and Σp,2, respectively. Knowing Sp,1, Sp,2, this article proposes a class of estimators for the spectrum (eigenvalues) of the matrix Σp,2Σp,1â1 as well as the pair of the whole matrices (Σp,1,Σp,2). The estimators are created based on Random Matrix Theory. Under mild conditions, our estimator for the spectrum of Σp,2Σp,1â1 is shown to be weakly consistent and the estimator for (Σp,1,Σp,2) is shown to be optimal in the sense of minimizing the asymptotic loss within the class of equivariant estimators as n1,n2,pââ with pân1âc1â(0,1), pân2âc2â(0,1)âª(1,â). Also, our estimators are easy to implement. Even when p is 1000, our estimators can be computed in seconds using a personallaptop.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Numerical Analysis
Authors
Jun Wen,