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.
Original language | English |
---|---|
Pages (from-to) | 222-232 |
Number of pages | 11 |
Journal | Journal of Multivariate Analysis |
Volume | 125 |
DOIs | |
Publication status | Published - Mar 2014 |
Scopus Subject Areas
- Statistics and Probability
- Numerical Analysis
- Statistics, Probability and Uncertainty
User-Defined Keywords
- High-dimensional data
- Large p small n
- Shrinkage estimator
- U-statistic