Bayesian treed Gaussian process models (tgp R package)
21/09/2007 -- by Robert B. Gramacy and Matt A. Taddy
tgp is an R package for fully Bayesian nonstationary, semiparametric nonlinear regression and design by treed Gaussian processes with jumps to the limiting linear model.
- Bayesian linear models, CART, treed linear models, stationary separable and isotropic Gaussian processes also implemented
- Categorical inputs, sensitivity analysis, multi-resolution models and importance tempering are supported in (new) v2.0
- Includes methods for the (sequential) design of exeperiments under these models
- 1-d and 2-d plotting, with higher dimension projection and slice capabilities, and tree drawing functions are also provided for visualization of tgp-class output.
This software is licensed under the GNU Lesser Public License (LGPL), version 2 or later. See the change log and an archive of previous versions.
Obtaining tgp
- Obtain R from cran.r-project.org by selecting the version for your operating system.
- Install the tgp package, from within R. This
will download, install, and configure the tgp package for
you.
> install.packages("tgp")
- Optionally, install the akima, maptree, and combinat packages.
> install.packages(c("akima", "maptree", "combinat"))
- Load the library as you would for any R library.
> library(tgp)
Documentation
- The tgp
tutorial
is implemented
as a package vignette, authored in Sweave. The pdf can be
obtained from within R with the following code.
> vignette("tgp")
To obtain the source code contained in the vignette, use the Stangle command.
- See the package documentation. A pdf version of the
reference manual, or help pages, is also available.
The help pages can be accessed from within
R. Try starting with...
> help(package=tgp)
> ? btgp # follow the examples - I gave a poster at the Valencia 8 meeting (June 2006) which is a (very) condensed version of the tutorial, above.
> Stangle(vignette("tgp")$file)Each of the examples in the vignette are also available as a demo. For example, to get the demo corresponding the example for the exponential data, do:
> demo("exp", package="tgp")The demos were actually created using the Stangle command on the vignette sources. To see all available demos, type:
> demo(package="tgp")Version 2.x is accompanied by a new tutorial that is still under construction.
References
- tgp: An R Package for Bayesian Nonstationary, Semiparametric Nonlinear Regression and Design by Treed Gaussian Process Models. (2007) Journal of Statistical Software, volume 19(9). Snapshot of the R vignette for the tgp package as of June 2007.
- Bayesian treed Gaussian process models with an application to computer modeling. (2007) with Herbert K.H. Lee. To appear in JASA. Preprint on arXiv:0710.4536
- My Ph.D. thesis. More details than you need, all in one place.
- Parameter space exploration with Gaussian process trees with Herbert K. H. Lee and William G. Macready; International Conference on Machine Learning (ICML 2004) Banff, Canada.
Please send questions and comments to rbgramacy_AT (_ams_DOT_ucsc_DOT_edu). Enjoy!
Robert B. Gramacy -- 2006