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An R package VIGoR for joint estimation of multiple linear learners with variational Bayesian inference
SUMMARY: An R package that can implement multiple linear learners, including penalized regression and regression with spike and slab priors, in a single model has been developed. Solutions are obtained with fast minorize-maximization algorithms in the framework of variational Bayesian inference. Thi...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9191213/ https://www.ncbi.nlm.nih.gov/pubmed/35575313 http://dx.doi.org/10.1093/bioinformatics/btac328 |
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author | Onogi, Akio Arakawa, Aisaku |
author_facet | Onogi, Akio Arakawa, Aisaku |
author_sort | Onogi, Akio |
collection | PubMed |
description | SUMMARY: An R package that can implement multiple linear learners, including penalized regression and regression with spike and slab priors, in a single model has been developed. Solutions are obtained with fast minorize-maximization algorithms in the framework of variational Bayesian inference. This package helps to incorporate multimodal and high-dimensional explanatory variables in a single regression model. AVAILABILITY AND IMPLEMENTATION: The R package VIGoR (Variational Bayesian Inference for Genome-wide Regression) is available at the Comprehensive R Archive Network (CRAN) (https://cran.r-project.org/) and at GitHub (https://github.com/Onogi/VIGoR). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-9191213 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-91912132022-06-14 An R package VIGoR for joint estimation of multiple linear learners with variational Bayesian inference Onogi, Akio Arakawa, Aisaku Bioinformatics Applications Notes SUMMARY: An R package that can implement multiple linear learners, including penalized regression and regression with spike and slab priors, in a single model has been developed. Solutions are obtained with fast minorize-maximization algorithms in the framework of variational Bayesian inference. This package helps to incorporate multimodal and high-dimensional explanatory variables in a single regression model. AVAILABILITY AND IMPLEMENTATION: The R package VIGoR (Variational Bayesian Inference for Genome-wide Regression) is available at the Comprehensive R Archive Network (CRAN) (https://cran.r-project.org/) and at GitHub (https://github.com/Onogi/VIGoR). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2022-05-16 /pmc/articles/PMC9191213/ /pubmed/35575313 http://dx.doi.org/10.1093/bioinformatics/btac328 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Applications Notes Onogi, Akio Arakawa, Aisaku An R package VIGoR for joint estimation of multiple linear learners with variational Bayesian inference |
title | An R package VIGoR for joint estimation of multiple linear learners with variational Bayesian inference |
title_full | An R package VIGoR for joint estimation of multiple linear learners with variational Bayesian inference |
title_fullStr | An R package VIGoR for joint estimation of multiple linear learners with variational Bayesian inference |
title_full_unstemmed | An R package VIGoR for joint estimation of multiple linear learners with variational Bayesian inference |
title_short | An R package VIGoR for joint estimation of multiple linear learners with variational Bayesian inference |
title_sort | r package vigor for joint estimation of multiple linear learners with variational bayesian inference |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9191213/ https://www.ncbi.nlm.nih.gov/pubmed/35575313 http://dx.doi.org/10.1093/bioinformatics/btac328 |
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