Learn R Programming
⚠️There's a newer version (1.1-19) of this package.Take me there.

spikeSlabGAM (version 1.1-7)

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.

Copy Link

Version

Install

install.packages('spikeSlabGAM')

Monthly Downloads

736

Version

1.1-7

License

CC BY-NC-SA 3.0

Maintainer

Fabian Scheipl

Last Published

February 24th, 2014

Functions in spikeSlabGAM (1.1-7)

fct

Generate design for a factor covariate
evalTerm

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

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

Summary for posterior of a spikeSlabGAM fit
rnd

Generate design for a random intercept
srf

Generate design for penalized surface estimation.
ssGAM2Bugs

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

Print summary for posterior of a spikeSlabGAM fit
ssGAMDesign

Generate design and model information for spikeSlabGAM
getPosteriorTerm

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

Generate orthogonal polynomial base for a numeric covariate without intercept
u

Generate design for an always included covariate
plotTerm

Plot the estimated effect of a model term.
plot.spikeSlabGAM

Generates graphical summaries of a fitted model
sm

Generate a reparameterized P-spline base
mrf

Generate design for a 2-D Gaussian Markov Random Field