Package: kergp
Type: Package
Title: Gaussian Process Laboratory
Version: 0.5.1
Date: 2020-02-05
Author: Yves Deville, David Ginsbourger, Olivier Roustant. Contributors: Nicolas Durrande.
Maintainer: Olivier Roustant <roustant@insa-toulouse.fr>
Description: Gaussian process regression with an emphasis on kernels.
    Quantitative and qualitative inputs are accepted. Some
    pre-defined kernels are available, such as radial or tensor-sum
    for quantitative inputs, and compound symmetry, low rank, group
    kernel for qualitative inputs. The user can define new kernels
    and composite kernels through a formula mechanism. Useful methods
    include parameter estimation by maximum likelihood, simulation,
    prediction and leave-one-out validation.
License: GPL-3
Depends: Rcpp (>= 0.10.5), methods, testthat, nloptr, lattice
Suggests: DiceKriging, DiceDesign, lhs, inline, foreach, knitr,
        ggplot2, reshape2, corrplot
Imports: MASS, numDeriv, stats4, doParallel, doFuture, utils
LinkingTo: Rcpp
RoxygenNote: 6.0.1
Collate: 'CovFormulas.R' 'allGenerics.R' 'checkGrad.R' 'covComp.R'
        'covMan.R' 'covQual.R' 'q1CompSymm.R' 'q1Symm.R' 'q1LowRank.R'
        'covQualNested.R' 'covQualOrd.R' 'covRadial.R' 'covTS.R'
        'covZZAll.R' 'gp.R' 'kFuns.R' 'kernelNorm.R' 'kernels1d_Call.R'
        'logLikFuns.R' 'methodGLS.R' 'methodMLE.R' 'miscUtils.R'
        'prinKrige.R' 'q1Diag.R' 'simulPar.R' 'simulate_gp.R'
        'warpFuns.R'
NeedsCompilation: yes
Packaged: 2020-02-05 09:16:55 UTC; yves
Repository: CRAN
Date/Publication: 2020-02-05 14:20:05 UTC
Built: R 3.5.3; x86_64-w64-mingw32; 2020-04-22 07:53:25 UTC; windows
Archs: i386, x64
