bsamGP: Bayesian Spectral Analysis Models using Gaussian Process Priors

Contains functions to perform Bayesian inference using a spectral analysis of Gaussian process priors. Gaussian processes are represented with a Fourier series based on cosine basis functions. Currently the package includes parametric linear models, partial linear additive models with/without shape restrictions, generalized linear additive models with/without shape restrictions, and density estimation model. To maximize computational efficiency, the actual Markov chain Monte Carlo sampling for each model is done using codes written in FORTRAN 90.

Version: 1.0.1
Imports: MASS, ggplot2, gridExtra
Published: 2017-08-06
Author: Seongil Jo [aut, cre], Taeryon Choi [aut], Beomjo Park [aut, cre], Peter J. Lenk [ctb]
Maintainer: Beomjo Park <beomjo at korea.ac.kr>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://statlab2.korea.ac.kr/software/bsam
NeedsCompilation: yes
CRAN checks: bsamGP results

Downloads:

Reference manual: bsamGP.pdf
Package source: bsamGP_1.0.1.tar.gz
Windows binaries: r-devel: bsamGP_1.0.1.zip, r-release: bsamGP_1.0.1.zip, r-oldrel: bsamGP_1.0.1.zip
OS X El Capitan binaries: r-release: bsamGP_1.0.1.tgz
OS X Mavericks binaries: r-oldrel: bsamGP_1.0.1.tgz
Old sources: bsamGP archive

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