Open Access
April 2016 Optimal shrinkage estimation of mean parameters in family of distributions with quadratic variance
Xianchao Xie, S. C. Kou, Lawrence Brown
Ann. Statist. 44(2): 564-597 (April 2016). DOI: 10.1214/15-AOS1377

Abstract

This paper discusses the simultaneous inference of mean parameters in a family of distributions with quadratic variance function. We first introduce a class of semiparametric/parametric shrinkage estimators and establish their asymptotic optimality properties. Two specific cases, the location-scale family and the natural exponential family with quadratic variance function, are then studied in detail. We conduct a comprehensive simulation study to compare the performance of the proposed methods with existing shrinkage estimators. We also apply the method to real data and obtain encouraging results.

Citation

Download Citation

Xianchao Xie. S. C. Kou. Lawrence Brown. "Optimal shrinkage estimation of mean parameters in family of distributions with quadratic variance." Ann. Statist. 44 (2) 564 - 597, April 2016. https://doi.org/10.1214/15-AOS1377

Information

Received: 1 February 2015; Revised: 1 August 2015; Published: April 2016
First available in Project Euclid: 17 March 2016

zbMATH: 1347.60017
MathSciNet: MR3476610
Digital Object Identifier: 10.1214/15-AOS1377

Subjects:
Primary: 60K35

Keywords: asymptotic optimality , hierarchical model , location-scale family , NEF-QVF , quadratic variance function , shrinkage estimator , unbiased estimate of risk

Rights: Copyright © 2016 Institute of Mathematical Statistics

Vol.44 • No. 2 • April 2016
Back to Top