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spikeSlabGAM (version 1.0-0)

Bayesian variable selection and model choice for generalized additive mixed models

Description

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

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Version

Install

install.packages('spikeSlabGAM')

Monthly Downloads

736

Version

1.0-0

License

GPL (>= 2)

Maintainer

Fabian Scheipl

Last Published

September 7th, 2011

Functions in spikeSlabGAM (1.0-0)

getPosteriorTerm

Get the posterior distribution of the linear predictor of a model term...

plot.spikeSlabGAM

Generates graphical summaries of a fitted model...

predict.spikeSlabGAM

Obtain posterior predictive/credible intervals from a spike-and-slab model...

plotTerm

Plot the estimated effect of a model term.

lin

Generate orthogonal polynomial base for a numeric covariate...

spikeSlabGAM

Generate posterior samples for a GAMM with spike-and-slab priors...

fct

Generate design for a factor covariate...

Generate a reparameterized P-spline base...

evalTerm

Get summaries of the posterior (predictive) distribution of the linear predictor of a model term...

srf

Generate design for penalized surface estimation.

rnd

Generate design for a random intercept...

ssGAM2Bugs

Convert samples from a model fitted with spikeSlabGAM into a bugs-object...

spikeAndSlab

Set up and sample a spike-and-slab prior model.

arrange.ggplots

Arrange multiple ggplots on the same device, trying to align axes etc.

mrf

Generate design for a 2-D Gaussian Markov Random Field...

Generate design for an always included covariate...

ssGAMDesign

Generate design and model information for spikeSlabGAM...

print.summary.spikeSlabGAM

Print summary for posterior of a spikeSlabGAM fit...

summary.spikeSlabGAM

Summary for posterior of a spikeSlabGAM fit...