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spikeSlabGAM (version 1.1-0)

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

1.1-0

License

GPL (>= 2)

Maintainer

Fabian Scheipl

Last Published

March 13th, 2012

Functions in spikeSlabGAM (1.1-0)

fct

Generate design for a factor covariate
print.summary.spikeSlabGAM

Print summary for posterior of a spikeSlabGAM fit
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
ssGAM2Bugs

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

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

Plot the estimated effect of a model term.
u

Generate design for an always included covariate
mrf

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

Summary for posterior of a spikeSlabGAM fit
sm

Generate a reparameterized P-spline base
ssGAMDesign

Generate design and model information for spikeSlabGAM
spikeSlabGAM

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

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

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

Generate orthogonal polynomial base for a numeric covariate without intercept
srf

Generate design for penalized surface estimation.
plot.spikeSlabGAM

Generates graphical summaries of a fitted model