Bayesian Variable Selection and Model Averaging in High-Dimensional Multinomial Nonparametric Regression
This article presents a Bayesian method for estimating nonparametrically a high-dimensional multinomial regression model. The regression functions are expressed as sums of main effects and interactions and our approach is able to select the significant components entering the model. Each of the main...
| Veröffentlicht in: | Journal of Computational and Graphical Statistics. - American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America, 1992. - 12(2003), 1, Seite 23-54 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
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2003
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| Zugriff auf das übergeordnete Werk: | Journal of Computational and Graphical Statistics |
| Schlagworte: | Classification Markov chain Monte Carlo Radial basis functions Information science Social sciences Mathematics Applied sciences Health sciences |
| Online verfügbar |
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