Abstract
It is known that, ordinarily, any admissible decision procedure for a statistical decision problem is, in a fairly strong sense, a limit of Bayes procedures, and in many cases such a limit must be a formal Bayes procedure with respect to a prior measure which may be improper (unbounded). This paper is, for the most part, a non-rigorous attempt at finding, in a reasonably explicit form, conditions for such a formal Bayes procedure to be admissible. In addition, a small amount of effort is devoted to the question of approximation of improper prior measures by prior probability measures without regard to the question of admissibility.
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Stein, C. (1965). Approximation of Improper Prior Measures by Prior Probability Measures. In: Neyman, J., Le Cam, L.M. (eds) Bernoulli 1713, Bayes 1763, Laplace 1813. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-49749-0_13
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DOI: https://doi.org/10.1007/978-3-642-49749-0_13
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