Article ID Journal Published Year Pages File Type
4636626 Applied Mathematics and Computation 2007 7 Pages PDF
Abstract

The problem of obtaining a flexible and easy to implement algorithm in order to derive the optimal sample size when the data are subject to misclassification is critical to practitioners. The topic is addressed from the Bayesian point of view where a special structure of the a priori parameter information is investigated. The proposed methodology is applied in specific examples.

Related Topics
Physical Sciences and Engineering Mathematics Applied Mathematics
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