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Bayesian Generalized Low Rank Regression Models for Neuroimaging Phenotypes and Genetic Markers
We propose a Bayesian generalized low rank regression model (GLRR) for the analysis of both high-dimensional responses and covariates. This development is motivated by performing searches for associations between genetic variants and brain imaging phenotypes. GLRR integrates a low rank matrix to app...
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| Autori principali: | , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2014
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4208701/ https://ncbi.nlm.nih.gov/pubmed/25349462 |
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