Non-parametric shrinkage mean estimation for quadratic loss functions with unknown covariance matrices

Authors:
Cheng Wang;Tiejun Tong;Longbing Cao;Baiqi Miao
Affiliations:
-;-;-;-
Venue:
Journal of Multivariate Analysis
Year:
2014

Citing 3
Cited 0

Robust shrinkage estimation for elliptically symmetric distributions with unknown covariance matrix

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A well-conditioned estimator for large-dimensional covariance matrices

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Improved mean estimation and its application to diagonal discriminant analysis

Bioinformatics

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Abstract

In this paper, a shrinkage estimator for the population mean is proposed under known quadratic loss functions with unknown covariance matrices. The new estimator is non-parametric in the sense that it does not assume a specific parametric distribution for the data and it does not require the prior information on the population covariance matrix. Analytical results on the improvement of the proposed shrinkage estimator are provided and some corresponding asymptotic properties are also derived. Finally, we demonstrate the practical improvement of the proposed method over existing methods through extensive simulation studies and real data analysis.