effectFusion: Bayesian Effect Fusion for Categorical Predictors
Version 1.0

Variable selection and Bayesian effect fusion for categorical predictors in linear regression models. Effect fusion aims at the question which categories have a similar effect on the response and therefore can be fused to obtain a sparser representation of the model. Effect fusion and variable selection can be obtained either with a prior that has an interpretation as spike and slab prior on the level effect differences or with a sparse finite mixture prior on the level effects. The regression coefficients are estimated with a flat uninformative prior after model selection or model averaged. For posterior inference, an MCMC sampling scheme is used that involves only Gibbs sampling steps.

AuthorDaniela Pauger [aut, cre], Helga Wagner [aut], Gertraud Malsiner-Walli [aut]
Date of publication2016-11-29 12:43:49
MaintainerDaniela Pauger <daniela.pauger@jku.at>
LicenseGPL-3
Version1.0
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("effectFusion")

Popular man pages

dic: DIC
effectFusion: Bayesian effect fusion for categorical predictors
model: Selected model of a 'fusion' object
plot.fusion: Plot an object of class 'fusion'
print.fusion: Print object of class 'fusion'
sim1: Simulated data set 1
sim2: Simulated data set 2
See all...

All man pages Function index File listing

Man pages

dic: DIC
effectFusion: Bayesian effect fusion for categorical predictors
model: Selected model of a 'fusion' object
plot.fusion: Plot an object of class 'fusion'
print.fusion: Print object of class 'fusion'
sim1: Simulated data set 1
sim2: Simulated data set 2
summary.fusion: Summary of object of class 'fusion'

Functions

coding Source code
correctRest Source code
createModel Source code
createModelvars Source code
createPrior Source code
createRowNames Source code
createSelmat Source code
dic Man page Source code
effectFusion Man page Source code
fusionVector Source code
getA Source code
getADiag Source code
getFusion Source code
getGamma Source code
getReparmats Source code
getSNominal Source code
getSOrdinal Source code
hpdMCMC Source code
inclProb Source code
mcmcLinreg Source code
mcmcMix Source code
mcmcSs Source code
model Man page Source code
modelRefit Source code
plot.fusion Man page Source code
plotHPD Source code
print.fusion Man page Source code
selectModel Source code
sim1 Man page
sim2 Man page
summary.fusion Man page Source code

Files

NAMESPACE
data
data/sim1.RData
data/sim2.RData
R
R/model_refit.R
R/model.R
R/sim1.R
R/create_modelvars.R
R/get_S_ordinal.R
R/plot.R
R/get_fusion.R
R/create_model.R
R/dic.R
R/create_selmat.R
R/getA_diag.R
R/get_gamma.R
R/sampler_ss.R
R/create_prior_par.R
R/hpd_mcmc.R
R/create_row_names.R
R/fusion_vector.R
R/corr_rest.R
R/print.R
R/coding.R
R/select_model.R
R/mcmc_linreg.R
R/get_reparm_mats.R
R/hpd_ggplot.R
R/incl_prob.R
R/effect_fusion.R
R/summary.R
R/sampler_mix.R
R/sim2.R
R/get_S_nominal.R
R/getA.R
MD5
DESCRIPTION
man
man/sim2.Rd
man/plot.fusion.Rd
man/model.Rd
man/effectFusion.Rd
man/summary.fusion.Rd
man/print.fusion.Rd
man/dic.Rd
man/sim1.Rd
effectFusion documentation built on May 20, 2017, 5:39 a.m.

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