BayesVarSel: Bayes Factors, Model Choice and Variable Selection in Linear Models
Version 1.7.0

Conceived to calculate Bayes factors in linear models and then to provide a formal Bayesian answer to testing and variable selection problems. From a theoretical side, the emphasis in this package is placed on the prior distributions and it allows a wide range of them: Jeffreys (1961); Zellner and Siow(1980); Zellner and Siow(1984); Zellner (1986); Fernandez et al. (2001); Liang et al. (2008) and Bayarri et al. (2012). The interaction with the package is through a friendly interface that syntactically mimics the well-known lm() command of R. The resulting objects can be easily explored providing the user very valuable information (like marginal, joint and conditional inclusion probabilities of potential variables; the highest posterior probability model, HPM; the median probability model, MPM) about the structure of the true -data generating- model. Additionally, this package incorporates abilities to handle problems with a large number of potential explanatory variables through parallel and heuristic versions of the main commands, Garcia-Donato and Martinez-Beneito (2013).

Getting started

Package details

AuthorGonzalo Garcia-Donato and Anabel Forte
Date of publication2016-11-18 12:47:45
MaintainerAnabel Forte <>
Package repositoryView on CRAN
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BayesVarSel documentation built on May 30, 2017, 4:42 a.m.