Article

High-dimensional Bayesian phenotype classification and model selection using genomic predictors

2019-09-23

Abstract excerpt

<h4>Motivation</h4> In this paper we describe a Bayesian hierarchical model termed ‘PMMLogit’ for classification and model selection in high-dimensional settings with binary phenotypes as outcomes. Posterior computation in the logistic model is known to be computationally demanding due to its non-conjugacy with common priors. We combine a Polya-Gamma based data augmentation strategy and use recent results on Mark...

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Literature Corpus work: 3d8d8659-dfa0-55f8-96ce-76b5cfee0745
DOI: 10.1101/778472

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