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Spiked Dirichlet Process Priors for Gaussian Process Models
We expand a framework for Bayesian variable selection for Gaussian process (GP) models by employing spiked Dirichlet process (DP) prior constructions over set partitions containing covariates. Our approach results in a nonparametric treatment of the distribution of the covariance parameters of the G...
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| Main Authors: | , |
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| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
2010
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| Fag: | |
| Online adgang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3742051/ https://ncbi.nlm.nih.gov/pubmed/23950763 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2010/201489 |
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