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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. For details and tutorials, see Gramacy (2007) <doi:10.18637/jss.v019.i09> and Gramacy & Taddy (2010) <doi:10.18637/jss.v033.i06>.
| Version: | 2.4-23 |
| Depends: | R (≥ 2.14.0) |
| Imports: | maptree |
| Suggests: | MASS |
| Published: | 2024-09-03 |
| DOI: | 10.32614/CRAN.package.tgp |
| Author: | Robert B. Gramacy [aut, cre], Matt A. Taddy [aut] |
| Maintainer: | Robert B. Gramacy <rbg at vt.edu> |
| License: | LGPL-2 | LGPL-2.1 | LGPL-3 [expanded from: LGPL] |
| URL: | https://bobby.gramacy.com/r_packages/tgp/ |
| NeedsCompilation: | yes |
| Citation: | tgp citation info |
| Materials: | README ChangeLog |
| In views: | Bayesian, ExperimentalDesign, MachineLearning, Spatial |
| CRAN checks: | tgp results |
| Reference manual: | tgp.pdf |
| Vignettes: |
a guide to the tgp package (source, R code) new features in tgp version 2.x (source, R code) |
| Package source: | tgp_2.4-23.tar.gz |
| Windows binaries: | r-devel: tgp_2.4-23.zip, r-release: tgp_2.4-23.zip, r-oldrel: tgp_2.4-23.zip |
| macOS binaries: | r-release (arm64): tgp_2.4-23.tgz, r-oldrel (arm64): tgp_2.4-23.tgz, r-release (x86_64): tgp_2.4-23.tgz, r-oldrel (x86_64): tgp_2.4-23.tgz |
| Old sources: | tgp archive |
| Reverse depends: | earlywarnings, plgp |
| Reverse imports: | c060, laGP, penalizedSVM, RNCEP, stops |
| Reverse suggests: | BayesTreePrior, dynaTree, mlr, rmi, ssr |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.