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

spikeSlabGAM (version 1.1-18)

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

686

Version

1.1-18

License

CC BY-NC-SA 4.0

Issues

1

Pull Requests

0

Stars

14

Forks

3

Maintainer

Fabian Scheipl

Last Published

May 30th, 2022

Functions in spikeSlabGAM (1.1-18)

ssGAM2Bugs

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

Generate design for an always included covariate
summary.spikeSlabGAM

Summary for posterior of a spikeSlabGAM fit
rnd

Generate design for a random intercept
ssGAMDesign

Generate design and model information for spikeSlabGAM
spikeAndSlab

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

Plot the estimated effect of a model term.
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
print.summary.spikeSlabGAM

Print summary for posterior of a spikeSlabGAM fit
lin

Generate orthogonal polynomial base for a numeric covariate without intercept
mrf

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

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

Generate design for a factor covariate
plot.spikeSlabGAM

Generates graphical summaries of a fitted model