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
