Fast Bayesian Gaussian Process Regression Fitting

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Documentation for package ‘BayesGPfit’ version 0.1.0

Help Pages Regular Bayesian fitting of Gaussian process regression on regular grid points with the modified exponential sqaured kernel.
GP.create.cols Create 256 colors graduately transitioning from Blue to Yellow to Red. Compute eigen functions
GP.eigen.value Compute eigen values for the standard modified exponential squared correlation kernel. 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 Simulate curve 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