Department of Mathematics
Non-parametric shrinkage mean estimation for quadratic loss functions with unknown covariance matrices
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. © 2014 Elsevier Inc.
High-dimensional data, Large p small n, Shrinkage estimator, U-statistic
Source Publication Title
Journal of Multivariate Analysis
Link to Publisher's Edition
Wang, Cheng, Tiejun Tong, Longbing Cao, and Baiqi Miao. "Non-parametric shrinkage mean estimation for quadratic loss functions with unknown covariance matrices." Journal of Multivariate Analysis 125 (2014): 222-232.