sdPrior: Scale-Dependent Hyperpriors in Structured Additive Distributional Regression

Utility functions for scale-dependent and alternative hyperpriors. The distribution parameters may capture location, scale, shape, etc. and every parameter may depend on complex additive terms (fixed, random, smooth, spatial, etc.) similar to a generalized additive model. Hyperpriors for all effects can be elicitated within the package. Including complex tensor product interaction terms and variable selection priors. The basic model is explained in in Klein and Kneib (2016) <doi:10.1214/15-BA983>.

Version: 0.5
Depends: R (≥ 3.1.0)
Imports: splines, GB2, caTools, MASS, stats, pscl, mvtnorm, mgcv, graphics, rsvd, doParallel, parallel, BayesX
Published: 2018-05-29
Author: Nadja Klein [aut, cre], Thomas Kneib [aut]
Maintainer: Nadja Klein <n.klein at mbs.edu>
License: GPL-2
NeedsCompilation: no
CRAN checks: sdPrior results

Downloads:

Reference manual: sdPrior.pdf
Package source: sdPrior_0.5.tar.gz
Windows binaries: r-devel: sdPrior_0.5.zip, r-release: sdPrior_0.5.zip, r-oldrel: sdPrior_0.5.zip
OS X binaries: r-release: sdPrior_0.5.tgz, r-oldrel: sdPrior_0.5.tgz
Old sources: sdPrior archive

Reverse dependencies:

Reverse suggests: bamlss

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