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Spiked Dirichlet Process Prior for Bayesian Multiple Hypothesis Testing in Random Effects Models
We propose a Bayesian method for multiple hypothesis testing in random effects models that uses Dirichlet process (DP) priors for a nonparametric treatment of the random effects distribution. We consider a general model formulation which accommodates a variety of multiple treatment conditions. A key...
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| Auteurs principaux: | , , |
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| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
2009
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3741668/ https://ncbi.nlm.nih.gov/pubmed/23950766 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1214/09-BA426 |
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