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).
- Version1.2.5
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- bsamGP citation info
- Last release03/18/2024
Documentation
Team
Beomjo Park
Seongil Jo
Show author detailsRolesAuthor, MaintainerTaeryon Choi
Show author detailsRolesAuthorPeter J. Lenk
Show author detailsRolesContributor
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- Imports3 packages