Approximate Gaussian Processes Using the Fourier Basis
Description
Routines for creating, manipulating, and performing
Bayesian inference about Gaussian processes in
one and two dimensions using the Fourier basis approximation:
simulation and plotting of processes, calculation of
coefficient variances, calculation of process density,
coefficient proposals (for use in MCMC). It uses R environments to
store GP objects as references/pointers.