A Bayesian Method for Classification and Discrimination
We discuss Bayesian analyses of traditional normal-mixture models for classification and discrimination. The development involves application of an iterative resampling approach to Monte Carlo inference, commonly called Gibbs sampling, and demonstrates routine application. We stress the benefits of...
| Veröffentlicht in: | The Canadian Journal of Statistics / La Revue Canadienne de Statistique. - Statistical Society of Canada / Société statistique du Canada. - 20(1992), 4, Seite 451-461 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
1992
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| Zugriff auf das übergeordnete Werk: | The Canadian Journal of Statistics / La Revue Canadienne de Statistique |
| Schlagworte: | Bayesian computations Classification Discrimination Mixtures of normals Posterior sampling Behavioral sciences Political science Mathematics Physical sciences Applied sciences |
| Online verfügbar |
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