[R-pkgs] spikeSlabGAM

From: Fabian Scheipl <Fabian.Scheipl_at_stat.uni-muenchen.de>
Date: Wed, 27 Apr 2011 09:32:32 +0200


spikeSlabGAM_0.9-6 (initial public release)

spikeSlabGAM implements Bayesian variable selection, model choice, and regularized estimation in (geo-)additive mixed models for Gaussian, binomial, and Poisson responses.

Its purpose is (1) to choose an appropriate subset of potential covariates and their interactions, (2) to determine whether linear or more flexible functional forms (P-splines, tensor product splines) are required to model the (joint) effects of the respective covariates, and (3) to fit these regularized effects and return (model-averaged) estimates.

Selection and regularization of the model terms is based on a novel spike-and-slab-type prior on coefficient groups associated with parametric and semi-parametric effects. Inference is fully Bayesian with an underlying MCMC sampler implemented in C and can take advantage of multi-core processors via multicore or snow. The package uses standard formula syntax so that complex models can be specified very concisely. It features powerful and user friendly visualizations using ggplot2.



Fabian Scheipl
Department of Statistics
Ludwig-Maximilians-University Munich
Ludwigstr. 33, room 239
80539 Munich
Germany
Phone: +49-89-2180-2284
http://www.statistik.lmu.de/~scheipl/

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