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>.

Install the latest version of this package by entering the following in R:

`install.packages("BayesVarSel")`

Author | Gonzalo Garcia-Donato and Anabel Forte |

Date of publication | 2016-11-18 12:47:45 |

Maintainer | Anabel Forte <anabel.forte@uv.es> |

License | GPL-2 |

Version | 1.7.0 |

**BMAcoeff:** Bayesian Model Averaged estimations of regression...

**Btest:** Bayes factors and posterior probabilities for linear...

**Bvs:** Bayesian Variable Selection for linear regression models

**GibbsBvs:** Bayesian Variable Selection for linear regression models...

**Hald:** Hald data

**Jointness:** Computation of Jointness measurements.

**Ozone35:** Ozone35 dataset

**PBvs:** Bayesian Variable Selection for linear regression models...

**predictBvs:** Bayesian Model Averaged predictions

src

src/Gibbsauxiliaryfuncs.h

src/Makevars

src/priorprob.c

src/priorprob.h

src/main.c

src/allBF.h

src/Gibbsauxiliaryfuncs.c

src/auxiliaryfuncs.c

src/auxiliaryfuncs.h

src/allBF.c

src/mainGibbs.c

src/mainSingle.c

NAMESPACE

demo

demo/00Index

demo/BayesVarSel.Hald.R
data

data/Ozone35.rda

data/Hald.rda

R

R/histBMA.R
R/onAtUn.R
R/GibbsBvs.R
R/print.Btest.R
R/Bvs.R
R/PBvs.R
R/summary.Bvs.R
R/print.jointness.R
R/Jointness.R
R/print.summary.Bvs.R
R/BMAcoeff.R
R/plotBvs.R
R/Btest.R
R/predictBvs.R
R/print.Bvs.R
MD5

DESCRIPTION

man

man/Btest.Rd
man/GibbsBvs.Rd
man/BMAcoeff.Rd
man/PBvs.Rd
man/Jointness.Rd
man/plotbvs.rd

man/histBMA.rd

man/predictBvs.Rd
man/Hald.Rd
man/Bvs.Rd
man/bayesvarsel-package.rd

man/Ozone35.Rd
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