Article ID Journal Published Year Pages File Type
1150213 Journal of Statistical Planning and Inference 2007 6 Pages PDF
Abstract
A Bayesian design criterion for selection experiments in plant breeding is derived using a utility function that minimizes the risk of an incorrect selection. A prior distribution on the heritability parameter is used to complete the definition of the design optimality criterion. An example is given with evaluations of the criterion for different prior distributions on the heritability. Though coming from a genetic motivation this criterion should prove useful for any other types of experiments with random treatment effects.
Related Topics
Physical Sciences and Engineering Mathematics Applied Mathematics
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