Learn R Programming

spikeSlabGAM (version 1.1-19)

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 stochastic search variable selection with spike-and-slab priors.

Copy Link

Version

Install

install.packages('spikeSlabGAM')

Monthly Downloads

618

Version

1.1-19

License

MIT + file LICENSE

Issues

1

Pull Requests

0

Stars

14

Forks

3

Maintainer

Fabian Scheipl

Last Published

June 10th, 2022

Functions in spikeSlabGAM (1.1-19)

fct

Generate design for a factor covariate
lin

Generate orthogonal polynomial base for a numeric covariate without intercept
getPosteriorTerm

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

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

Print summary for posterior of a spikeSlabGAM fit
rnd

Generate design for a random intercept
summary.spikeSlabGAM

Summary for posterior of a spikeSlabGAM fit
plotTerm

Plot the estimated effect of a model term.
ssGAM2Bugs

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

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

Generate design and model information for spikeSlabGAM
u

Generate design for an always included covariate
plot.spikeSlabGAM

Generates graphical summaries of a fitted model
srf

Generate design for penalized surface estimation.
spikeSlabGAM

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

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

Generate a reparameterized P-spline base
spikeAndSlab

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