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Weighted covariance matrix estimation

Author

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  • Yang, Guangren
  • Liu, Yiming
  • Pan, Guangming

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.

Suggested Citation

  • Yang, Guangren & Liu, Yiming & Pan, Guangming, 2019. "Weighted covariance matrix estimation," Computational Statistics & Data Analysis, Elsevier, vol. 139(C), pages 82-98.
    • Handle: RePEc:eee:csdana:v:139:y:2019:i:c:p:82-98
    DOI: 10.1016/j.csda.2019.04.017
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    References listed on IDEAS

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