Fast Bayesian Gaussian Process Regression Fitting

Documentation for package ‘BayesGPfit’ version 1.1.0

GP.Bayes.fit	Regular Bayesian fitting of Gaussian process regression on regular grid points with the modified exponential sqaured kernel.
GP.create.cols	Create 256 colors gradually transitioning from Blue to Yellow to Red.
GP.eigen.funcs.fast	Compute eigen functions
GP.eigen.funcs.fast.orth	Create orthogonal eigen functions
GP.eigen.value	Compute eigen values for the standard modified exponential squared correlation kernel.
GP.fast.Bayes.fit	Fast Bayesian fitting of Gaussian process
GP.generate.grids	Create spatial grids.
GP.plot.curve	Graphical representation of one, two, three-dimensional curves
GP.plot.curves	Graphical representation of multiple curves in one and two-dimensional curves
GP.predict	Gaussian process predictions
GP.simulate.curve.fast	Simulate curve on d-dimensional Euclidean space based on Gaussian processes via modified exponential squared kernel.
GP.simulate.curves.fast	Simulate multiple curves on d-dimensional Euclidean space based on Gaussian processes via modified exponential squared kernel.
GP.std.grids	Compute the standardized grids
GP.summary	Summary of posterior inference on the Bayesian Gaussian process regression model