By Dasgupta A. (ed.)
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Additional info for A festschrift for Herman Rubin
The material in section 6 deals with this result, and the large related literature that has followed. In many problems, as in the previous paragraph, Bayes or Generalized Bayes estimators are known to form a complete class. When loss is quadratic and the prior (and hence typically the posterior) distribution is not degenerate at a point, the Bayes estimator cannot take values on the boundary of the parameter space. There are many results in the literature that use this phenomenon to determine inadmissibility of certain estimators that take values on (or near) the boundary.
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