Document Type

Journal Article

Department/Unit

Department of Mathematics

Title

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

Language

English

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. © 2014 Elsevier Inc.

Keywords

High-dimensional data, Large p small n, Shrinkage estimator, U-statistic

Publication Date

2014

Source Publication Title

Journal of Multivariate Analysis

Volume

125

Start Page

222

End Page

232

Publisher

Elsevier

DOI

10.1016/j.jmva.2013.12.012

Link to Publisher's Edition

http://dx.doi.org/10.1016/j.jmva.2013.12.012

ISSN (print)

0047259X

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