| tgp-package | The Treed Gaussian Process Model Package |
| bcart | Bayesian Nonparametric & Nonstationary Regression Models |
| bgp | Bayesian Nonparametric & Nonstationary Regression Models |
| bgpllm | Bayesian Nonparametric & Nonstationary Regression Models |
| blm | Bayesian Nonparametric & Nonstationary Regression Models |
| btgp | Bayesian Nonparametric & Nonstationary Regression Models |
| btgpllm | Bayesian Nonparametric & Nonstationary Regression Models |
| btlm | Bayesian Nonparametric & Nonstationary Regression Models |
| default.itemps | Default Sigmoidal, Harmonic and Geometric Temperature Ladders |
| dopt.gp | Sequential D-Optimal Design for a Stationary Gaussian Process |
| exp2d | 2-d Exponential Data |
| exp2d.rand | Random 2-d Exponential Data |
| exp2d.Z | Random Z-values for 2-d Exponential Data |
| fried.bool | First Friedman Dataset and a variation |
| friedman.1.data | First Friedman Dataset and a variation |
| hist2bar | Functions to plot summary information about the sampled inverse temperatures, tree heights, etc., stored in the traces of a "tgp"-class object |
| interp.loess | Lowess 2-d interpolation onto a uniform grid |
| itemps.barplot | Functions to plot summary information about the sampled inverse temperatures, tree heights, etc., stored in the traces of a "tgp"-class object |
| lhs | Latin Hypercube sampling |
| mapT | Plot the MAP partition, or add one to an existing plot |
| optim.ptgpf | Surrogate-based optimization of noisy black-box function |
| optim.step.tgp | Surrogate-based optimization of noisy black-box function |
| partition | Partition data according to the MAP tree |
| plot.tgp | Plotting for Treed Gaussian Process Models |
| predict.tgp | Predict method for Treed Gaussian process models |
| sens | Monte Carlo Bayesian Sensitivity Analysis |
| tgp.default.params | Default Treed Gaussian Process Model Parameters |
| tgp.design | Sequential Treed D-Optimal Design for Treed Gaussian Process Models |
| tgp.trees | Plot the MAP Tree for each height encountered by the Markov Chain |