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James-Stein Estimators

A class of estimators that arise from discovery of the remarkable fact that in a multivariate normal distribution with dimension at least three, the vector of sample means, x, may be an admissible estimator of the vector of population means, i.e. there are other estimators whose risk functions are everywhere smaller than the risk of x, where the risk function of an estimator is defined in terms of variance plus bias squared.

James-Stein Estimators

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