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

The 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.

Automated summary

An R package has been developed to implement multiple linear learners in a single model. It uses fast algorithms to obtain solutions and is useful for incorporating multimodal and high-dimensional explanatory variables in regression models.