Abstract
Abstract A well known intuitive justification for the James-Stein estimator of the mean vector of a multivariate normal distribution is that it is an empirical Bayes estimator. The prior distribution is multivariate normal with the mean vector O and covariance matrix equal to σ2 I where σ2 is unknown and is estimated from the data. Here, we derive a version of the James-Stein estimator of the location vector for an essentially arbitrary location family.
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