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).