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spikeSlabGAM (version 1.1-2)

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

1.1-2

License

GPL (>= 2)

Maintainer

Fabian Scheipl

Last Published

September 17th, 2012

Functions in spikeSlabGAM (1.1-2)

summary.spikeSlabGAM

Summary for posterior of a spikeSlabGAM fit
spikeAndSlab

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

Generate a reparameterized P-spline base
fct

Generate design for a factor covariate
print.summary.spikeSlabGAM

Print summary for posterior of a spikeSlabGAM fit
srf

Generate design for penalized surface estimation.
evalTerm

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

Generate orthogonal polynomial base for a numeric covariate without intercept
plot.spikeSlabGAM

Generates graphical summaries of a fitted model
u

Generate design for an always included covariate
ssGAM2Bugs

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

Plot the estimated effect of a model term.
mrf

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

Generate design for a random intercept
getPosteriorTerm

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

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

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

Generate design and model information for spikeSlabGAM