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An R package VIGoR for joint estimation of multiple linear learners with variational Bayesian inference

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Abstract 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… Click to show full abstract

Abstract 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.

Keywords: linear learners; bayesian inference; multiple linear; package; variational bayesian

Journal Title: Bioinformatics
Year Published: 2022

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