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Using a stochastic decision function in Bayesian sampling planning
Modelprojekt, 1. modul, 1997, id:198
Vejleder:
Findes på RUb: Ja
English abstract
In the following I have examined the use of a stochastic decision function in Bayesian sampling planning. More precisely I examined the problem of accepting or rejecting a batch of articles described by a normally distributed average weight. Such a decision can be made by using a polynomial loss function. If we let the loss function be linearly dependent on the size of the samlpe, we can find the optimal size of the sample. In this report I have examined the appliance of a stochastic decision function proposed by /Ho, 1995). The purpose of this decision function is to allow for the buyer to bargain after the sample have been tested. I have written a program in Mathematica that can find the optimal size of the sample and loss function. Results from this program show that the stochastic decision function does not have a great influcence on the minimizing sample size.

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