https://github.com/cran/tgp
Tip revision: 11424beac628f853fdd6fc9ae132f91bf42b8f0a authored by Robert B. Gramacy on 28 November 2023, 16:40:02 UTC
version 2.4-22
version 2.4-22
Tip revision: 11424be
DESCRIPTION
Package: tgp
Title: Bayesian Treed Gaussian Process Models
Version: 2.4-22
Date: 2023-11-27
Author: Robert B. Gramacy <rbg@vt.edu> and Matt A. Taddy
Depends: R (>= 2.14.0)
Imports: maptree
Suggests: MASS
Description: 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>.
Maintainer: Robert B. Gramacy <rbg@vt.edu>
License: LGPL
URL: https://bobby.gramacy.com/r_packages/tgp/
NeedsCompilation: yes
Packaged: 2023-11-27 20:54:05 UTC; bobby
Repository: CRAN
Date/Publication: 2023-11-28 16:40:02 UTC