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spikeSlabGAM: Bayesian Variable Selection and Model Choice for Generalized Additive Mixed Models

Bayesian variable selection, model choice, and regularized estimation for (spatial) generalized additive mixed regression models via stochastic search variable selection with spike-and-slab priors.

Version: 1.1-19
Depends: R (≥ 2.15.1)
Imports: coda, cluster, ggplot2 (≥ 2.0.0), gridExtra (≥ 2.0.0), interp, MASS, MCMCpack, mvtnorm, R2WinBUGS, reshape, scales, splines, parallel
Suggests: mboost, mlbench, gtable, knitr, rmarkdown
Published: 2022-06-10
Author: Fabian Scheipl [aut, cre], Bettina Gruen [ctb]
Maintainer: Fabian Scheipl <fabian.scheipl at stat.uni-muenchen.de>
License: MIT + file LICENSE
URL: https://github.com/fabian-s/spikeSlabGAM
NeedsCompilation: yes
Citation: spikeSlabGAM citation info
Materials: NEWS
In views: Bayesian
CRAN checks: spikeSlabGAM results

Documentation:

Reference manual: spikeSlabGAM.pdf
Vignettes: spikeSlabGAM: Bayesian Variable Selection, Model Choice and Regularization for Generalized Additive Mixed Models in R

Downloads:

Package source: spikeSlabGAM_1.1-19.tar.gz
Windows binaries: r-devel: spikeSlabGAM_1.1-19.zip, r-release: spikeSlabGAM_1.1-19.zip, r-oldrel: spikeSlabGAM_1.1-19.zip
macOS binaries: r-release (arm64): spikeSlabGAM_1.1-19.tgz, r-oldrel (arm64): spikeSlabGAM_1.1-19.tgz, r-release (x86_64): spikeSlabGAM_1.1-19.tgz, r-oldrel (x86_64): spikeSlabGAM_1.1-19.tgz
Old sources: spikeSlabGAM archive

Reverse dependencies:

Reverse imports: countSTAR, SeBR

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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