Bayesian nonstationary, semiparametric nonlinear regression and design by treed Gaussian processes with jumps to the limiting linear model (LLM). Special cases also implemented include Bayesian linear models, CART, treed linear models, stationary separable and isotropic Gaussian processes. 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, and a limited set of experimental design and adaptive sampling functions are also provided, including ALM, ALC, and expected improvement.
| Version: | 2.1-2 |
| Depends: | R (≥ 2.4) |
| Suggests: | akima, maptree, combinat |
| Date: | 2008-4-17 |
| Author: | Robert B. Gramacy and Matt A. Taddy |
| Maintainer: | Robert B. Gramacy <rbgramacy at ams.ucsc.edu> |
| License: | LGPL |
| URL: | http://www.ams.ucsc.edu/~rbgramacy/tgp.html |
| In views: | Bayesian, MachineLearning, Spatial |
| CRAN checks: | tgp results |
Downloads:
| Package source: | tgp_2.1-2.tar.gz |
| MacOS X binary: | tgp_2.1-2.tgz |
| Windows binary: | tgp_2.1-2.zip |
| Reference manual: | tgp.pdf |
| Vignettes: |
a guide to the tgp package new features in tgp version 2.x |
| News/ChangeLog: | ChangeLog |
| Old sources: | tgp archive |