predict.tgp
(Package: tgp) :
Predict method for Treed Gaussian process models
This generic prediction method was designed to obtain samples from the posterior predictive distribution after the b* functions have finished. Samples, or kriging mean and variance estimates, can be obtained from the MAP model encoded in the "tgp"-class object, or this parameterization can be used as a jumping-off point in obtaining further samples from the joint posterior and posterior predictive distributions
● Data Source:
CranContrib
● Keywords: models, nonlinear, nonparametric, smooth, spatial, tree
● Alias: predict.tgp
●
0 images
default.itemps
(Package: tgp) :
Default Sigmoidal, Harmonic and Geometric Temperature Ladders
Parameterized by the minimum desired inverse temperature, this function generates a ladder of inverse temperatures k[1:m] starting at k[1] = 1, with m steps down to the final temperature k[m] = k.min progressing sigmoidally, harmonically or geometrically. The output is in a format convenient for the b* functions in the tgp package (e.g. btgp), including stochastic approximation parameters c0 and n0 for tuning the uniform pseudo-prior output by this function
Generate X and Y values from the 10-dim “first” Friedman data set used to validate the Multivariate Adaptive Regression Splines (MARS) model, and a variation involving boolean indicators. This test function has three non-linear and interacting variables, along with two linear, and five which are irrelevant. The version with indicators has parts of the response turned on based on the setting of the indicators
The seven functions described below implement Bayesian regression models of varying complexity: linear model, linear CART, Gaussian process (GP), GP with jumps to the limiting linear model (LLM), treed GP, and treed GP LLM.
mapT
(Package: tgp) :
Plot the MAP partition, or add one to an existing plot
Plot the maximum a' posteriori (MAP) tree from a "tgp"-class object, or add one on top of an existing plot. Like plot.tgp, projections and slices of trees can be plotted as specified
● Data Source:
CranContrib
● Keywords: hplot, tree
● Alias: mapT
●
0 images
tgp.design
(Package: tgp) :
Sequential Treed D-Optimal Design for Treed Gaussian Process Models
Based on the maximum a' posteriori (MAP) treed partition extracted from a "tgp"-class object, calculate independent sequential treed D-Optimal designs in each of the regions.
● Data Source:
CranContrib
● Keywords: design, optimize, spatial, tree
● Alias: tgp.design
●
0 images
optim.tgp
(Package: tgp) :
Surrogate-based optimization of noisy black-box function
Optimize (minimize) a noisy black-box function (i.e., a function which may not be differentiable, and may not execute deterministically). A b*tgp model is used as a surrogate for adaptive sampling via improvement (and other) statistics. Note that this function is intended as a skeleton to be tailored as required for a particular application
plot.tgp
(Package: tgp) :
Plotting for Treed Gaussian Process Models
A generic function for plotting of "tgp"-class objects. 1-d posterior mean and error plots, 2-d posterior mean and error image and perspective plots, and 3+-dimensional mean and error image and perspective plots are supported via projection and slicing.
● Data Source:
CranContrib
● Keywords: hplot, tree
● Alias: plot.tgp
●
0 images
providing 
.