Package: tgp
Title: Bayesian treed Gaussian process models
Version: 2.3-1
Date: 2010-02-08
Author: Robert B. Gramacy <rbgramacy@ams.ucsc.edu> and Matt A. Taddy
        <taddy@ams.ucsc.edu>
Depends: R (>= 2.4)
Suggests: akima, maptree
Description: 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. 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.
Maintainer: Robert B. Gramacy <rbgramacy@ams.ucsc.edu>
License: LGPL
URL: http://www.ams.ucsc.edu/~rbgramacy/tgp.html
Repository: CRAN
Date/Publication: 2010-02-08 11:38:40
