tgp v2.4-17
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Bayesian Treed Gaussian Process Models
Bayesian nonstationary, semiparametric nonlinear regression
and design by treed Gaussian processes (GPs) with jumps to the limiting
linear model (LLM). Special cases also implemented include Bayesian
linear models, CART, treed linear models, stationary separable and
isotropic GPs, and GP single-index models. Provides 1-d and 2-d plotting functions
(with projection and slice capabilities) and tree drawing, designed for
visualization of tgp-class output. Sensitivity analysis and
multi-resolution models are supported. Sequential experimental
design and adaptive sampling functions are also provided, including ALM,
ALC, and expected improvement. The latter supports derivative-free
optimization of noisy black-box functions.
Functions in tgp
| Name | Description | |
| itemps | Functions to plot summary information about the sampled inverse temperatures, tree heights, etc., stored in the traces of a "tgp"-class object | |
| exp2d.Z | Random Z-values for 2-d Exponential Data | |
| friedman.1.data | First Friedman Dataset and a variation | |
| lhs | Latin Hypercube sampling | |
| dopt.gp | Sequential D-Optimal Design for a Stationary Gaussian Process | |
| default.itemps | Default Sigmoidal, Harmonic and Geometric Temperature Ladders | |
| exp2d.rand | Random 2-d Exponential Data | |
| btgp | Bayesian Nonparametric \& Nonstationary Regression Models | |
| tgp-internal | Internal Treed Gaussian Process Model Functions | |
| interp.loess | Lowess 2-d interpolation onto a uniform grid | |
| tgp.default.params | Default Treed Gaussian Process Model Parameters | |
| exp2d | 2-d Exponential Data | |
| mapT | Plot the MAP partition, or add one to an existing plot | |
| tgp.design | Sequential Treed D-Optimal Design for Treed Gaussian Process Models | |
| predict.tgp | Predict method for Treed Gaussian process models | |
| sens | Monte Carlo Bayesian Sensitivity Analysis | |
| optim.tgp | Surrogate-based optimization of noisy black-box function | |
| partition | Partition data according to the MAP tree | |
| tgp.trees | Plot the MAP Tree for each height encountered by the Markov Chain | |
| plot.tgp | Plotting for Treed Gaussian Process Models | |
| tgp-package | The Treed Gaussian Process Model Package | |
| No Results! | ||
Vignettes of tgp
| Name | ||
| motovate_bgp.pdf | ||
| motovate_btgp.pdf | ||
| tgp.Rnw | ||
| tgp.bib | ||
| tgp2.Rnw | ||
| tree.pdf | ||
| No Results! | ||
Last month downloads
Details
| Date | 2020-09-11 |
| License | LGPL |
| URL | https://bobby.gramacy.com/r_packages/tgp/ |
| NeedsCompilation | yes |
| Packaged | 2020-09-11 12:43:32 UTC; bobby |
| Repository | CRAN |
| Date/Publication | 2020-09-20 16:10:02 UTC |
| imports | maptree |
| suggests | MASS |
| depends | R (>= 2.14.0) |
| Contributors | Robert Gramacy, Matt Taddy |
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