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- Title
Trimmed estimators for large dimensional sparse covariance matrices.
- Authors
Yang, Guangren; Cui, Xia
- Abstract
In this paper, we will propose two new estimators for sparse covariance matrix. Our starting point is to make the estimator of each element of covariance matrix more robust. More precisely, we will trim the observations for each pairwise product of components of population as a first step. Then we form the sample covariance matrices based on the trimmed data. Finally, we apply the thresholding to the derived sample covariance matrices. These two new estimators will be shown to achieve the optimal convergence rate.
- Subjects
ANALYSIS of covariance; REGRESSION analysis; COVARIANCE matrices; MATRICES (Mathematics); ALGEBRA
- Publication
Random Matrices: Theory & Application, 2019, Vol 8, Issue 1, pN.PAG
- ISSN
2010-3263
- Publication type
Article
- DOI
10.1142/S2010326319500035