Data Analysis Using Stein's Estimator and its Generalizations
作者:
Bradley Efron,
Carl Morris,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1975)
卷期:
Volume 70,
issue 350
页码: 311-319
ISSN:0162-1459
年代: 1975
DOI:10.1080/01621459.1975.10479864
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
In 1961, James and Stein exhibited an estimator of the mean of a multivariate normal distribution having uniformly lower mean squared error than the sample mean. This estimator is reviewed briefly in an empirical Bayes context. Stein's rule and its generalizations are then applied to predict baseball averages, to estimate toxomosis prevalence rates, and to estimate the exact size of Pearson's chi-square test with results from a computer simulation. In each of these examples, the mean square error of these rules is less than half that of the sample mean.
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