Abstract
ABSTRACT In this paper we formulate a finite sequentially planned Bayesian multiple decision problem, thereby introducing a theory of optimal sampling for stochastic processes in continuous time as an alternative observation concept to stopping times, and elaborate the existence and the structure of a Bayes procedure for the sequentially planned observation of stochastic processes of the exponential class. The optimal procedure consists of a Bayesian terminal decision procedure (non-sequential part) and an optimal control variable (sequential part). Moreover, some properties of the Bayes procedure are considered.
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Schedule a callMore From: Communications in Statistics. Part C: Sequential Analysis
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