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How Many Samples?: A Bayesian Nonparametric Approach

Stephen G. Walker
Journal of the Royal Statistical Society. Series D (The Statistician)
Vol. 52, No. 4 (2003), pp. 475-482
Published by: Wiley for the Royal Statistical Society
Stable URL: http://www.jstor.org/stable/4128126
Page Count: 8
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How Many Samples?: A Bayesian Nonparametric Approach
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Abstract

The paper considers a Bayesian nonparametric decision theoretic approach to sample size calculations, where the ultimate goal is to make a terminal action from a finite set of actions. This terminal action is made via the maximization of expected utility, the maximization being made with respect to a probability measure on the states of nature. The probability measure depends on the amount of information, i.e. the number of samples collected. It is the prior in the case of no samples and the posterior when samples have been taken.

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