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spikeSlabGAM (version 1.1-5)

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

1.1-5

License

CC BY-NC-SA 3.0

Maintainer

Fabian Scheipl

Last Published

March 13th, 2013

Functions in spikeSlabGAM (1.1-5)

mrf

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

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

Generate a reparameterized P-spline base
spikeSlabGAM

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

Generate design for penalized surface estimation.
plot.spikeSlabGAM

Generates graphical summaries of a fitted model
u

Generate design for an always included covariate
summary.spikeSlabGAM

Summary for posterior of a spikeSlabGAM fit
lin

Generate orthogonal polynomial base for a numeric covariate without intercept
plotTerm

Plot the estimated effect of a model term.
rnd

Generate design for a random intercept
fct

Generate design for a factor covariate
spikeAndSlab

Set up and sample a spike-and-slab prior model.
print.summary.spikeSlabGAM

Print summary for posterior of a spikeSlabGAM fit
ssGAM2Bugs

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

Generate design and model information for spikeSlabGAM