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. This software has been developed using funding supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (no. NRF-2016R1D1A1B03932178 and no. NRF-2017R1D1A3B03035235).

Version: 1.1.0
Imports: MASS, ggplot2, gridExtra
Published: 2017-10-22
Author: Seongil Jo [aut, cre], Taeryon Choi [aut], Beomjo Park [aut, cre], Peter J. Lenk [ctb]
Maintainer: Beomjo Park <beomjo at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: README
CRAN checks: bsamGP results


Reference manual: bsamGP.pdf
Package source: bsamGP_1.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: bsamGP_1.1.0.tgz
OS X Mavericks binaries: r-oldrel: bsamGP_1.1.0.tgz
Old sources: bsamGP archive


Please use the canonical form to link to this page.