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Authors: Robert B. Gramacy
Title: [download]
(12567)
tgp: An R Package for Bayesian Nonstationary, Semiparametric Nonlinear Regression and Design by Treed Gaussian Process Models
Reference: Vol. 19, Issue 9, Jun 2007
Submitted 2006-07-12, Accepted 2007-06-13
Type: Article
Abstract:

The tgp package for R is a tool for fully Bayesian nonstationary, semiparametric nonlinear regression and design by treed Gaussian processes with jumps to the limiting linear model. Special cases also implemented include Bayesian linear models, linear CART, stationary separable and isotropic Gaussian processes. In addition to inference and posterior prediction, the package supports the (sequential) design of experiments under these models paired with several objective criteria. 1-d and 2-d plotting, with higher dimension projection and slice capabilities, and tree drawing functions (requiring maptree and combinat packages), are also provided for visualization of tgp objects.

Paper: [download]
(12567)
tgp: An R Package for Bayesian Nonstationary, Semiparametric Nonlinear Regression and Design by Treed Gaussian Process Models
(application/pdf, 2.1 MB)
Supplements: [download]
(1812)
tgp_1.2-5.tar.gz: R source package
(application/x-gzip, 3.3 MB)
[download]
(1594)
Examples.zip: R scripts with examples from the vignette
(application/x-zip-compressed, 5.1 KB)
Resources: BibTeX | OAI
Creative Commons License
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3)
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