INCOMPLETE PRIOR INFORMATION IN A CLASSIFICATION PROCEDURE.
FLORIDA STATE UNIV TALLAHASSEE DEPT OF STATISTICS
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The classification of specimens into one of N populations is considered when the observation on each specimen is a multivariate discrete random variable and when incomplete prior information is available concerning the occurrence of specimens from the various populations. The T-minimax decision criterion is applied and it is shown that an optimal classification procedure is the solution of a finite matrix game. The consistency of the T-minimax procedure is demonstrated when certain population probabilities are estmated by sample proportions. A medical example is considered. Author
- Medicine and Medical Research
- Statistics and Probability