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.


Reference manual

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1.0.1 by Beomjo Park, 2 months ago

Browse source code at

Authors: Seongil Jo [aut, cre], Taeryon Choi [aut], Beomjo Park [aut, cre], Peter J. Lenk [ctb]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports MASS, ggplot2, gridExtra

See at CRAN