Description: 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)<DOI:10.1007/bf02888369>; Zellner and Siow(1984); Zellner (1986)<DOI:10.2307/2233941>; Fernandez et al. (2001)<DOI:10.1016/S0304-4076(00)00076-2>; Liang et al. (2008)<DOI:10.1198/016214507000001337>  and Bayarri et al. (2012)<DOI:10.1214/12-aos1013>. 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)<DOI:10.1080/01621459.2012.742443>.

person("Gonzalo", "Garcia-Donato",    email = "garcia_gon@gva.es",    role = c("aut")),
person("Anabel", "Forte",             email = "anabel.forte@uv.es",   role = c("aut", "cre")),
person("Carlos", "Vergara-Hernández", email = "carlos.vergara@uv.es", role = c("ctb"))

Description: 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)<DOI:10.1007/bf02888369>; Zellner and Siow(1984); Zellner (1986)<DOI:10.2307/2233941>; Fernandez et al. (2001)<DOI:10.1016/s0304-4076(00)00076-2>; Liang et al. (2008)<DOI:10.1198/016214507000001337>  and Bayarri et al. (2012)<DOI:10.1214/12-aos1013>. 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)<DOI:10.1080/01621459.2012.742443>. It also allows problems with p>n and p>>n and also incorporates routines to handle problems with variable selection with factors.
Acknowledgements: since version 1.9.0 BayesVarSel uses the non-exported
function get_rdX from package lmerTest (distributed under
GPL-2, GPL-3) and authored by Alexandra Kuznetsova, Per Bruun
Brockhoff and Rune Haubo Bojesen Christensen.
Packaged: 2020-02-18 07:11:42 UTC; gonzalo.garciadonato