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Title: Weighted covariance matrix estimation
Authors: Yang, Guangren
Liu, Yiming
Pan, Guangming
Keywords: Science::Mathematics
Issue Date: 2019
Source: Yang, G., Liu, Y., & Pan, G. (2019). Weighted covariance matrix estimation. Computational Statistics & Data Analysis, 139, 82–98. doi:10.1016/j.csda.2019.04.017
Journal: Computational Statistics & Data Analysis 
Abstract: The paper proposes a cross-validated linear shrinkage estimation for population covariance matrices. Moreover we also propose a novel weighted estimator based on the thresholding and shrinkage methods for high dimensional datasets. It is applicable to a wider scope of different structures of covariance matrices. Some theoretical results about the cross-validated shrinkage method and weighted covariance estimation methods are also developed. The finite-sample performance of the proposed methods is illustrated through extensive simulations and real data analysis.
ISSN: 0167-9473
DOI: 10.1016/j.csda.2019.04.017
Schools: School of Physical and Mathematical Sciences 
Rights: © 2019 Elsevier B.V. All rights reserved. This paper was published in Computational Statistics & Data Analysis and is made available with permission of Elsevier B.V.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Journal Articles

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