# Bayesian Treed Gaussian Process Models

## Documentation for package ‘tgp’ version 2.4-23

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Code demos. Use demo() to run them.

## Help Pages

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