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VOL. 6 | 2010 Empirical Bayes in-season prediction of baseball batting averages
Wenhua Jiang, Cun-Hui Zhang

Editor(s) James O. Berger, T. Tony Cai, Iain M. Johnstone

Abstract

The performance of a number of empirical Bayes methods are examined for the in-season prediction of batting averages with the 2005 Major League baseball data. Among the methodologies considered are new general empirical Bayes estimators in homoscedastic and heteroscedastic partial linear models.

Information

Published: 1 January 2010
First available in Project Euclid: 26 October 2010

MathSciNet: MR2798524

Digital Object Identifier: 10.1214/10-IMSCOLL618

Subjects:
Primary: 62J05 , 62J07
Secondary: 62H12 , 62H25

Keywords: batting average , compound decisions , Empirical Bayes , hitting , nonparametric estimation , Partial linear model , Semiparametric estimation , sports

Rights: Copyright © 2010, Institute of Mathematical Statistics

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