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DiceKriging: Kriging methods for computer experiments

This repository is the regular DiceKriging package repository (available at http://cran.r-project.org/web/packages/DiceKriging). It contains the latest sources, possibly some supplement of stable CRAN release.

Installation

You can install the standard (CRAN) version of the code: install.packages("DiceKriging")

You can install the latest (this repository) version x.y.z of the code:

  • using pre-built packages:
    • Windows: install.packages("https://github.com/DiceKrigingClub/DiceKriging/releases/download/windows/DiceKriging_x.y.z.zip")
    • Linux: install.packages("https://github.com/DiceKrigingClub/DiceKriging/releases/download/osx-linux/DiceKriging_x.y.z.tar.gz")
    • OSX: install.packages("https://github.com/DiceKrigingClub/DiceKriging/releases/download/osx-linux/DiceKriging_x.y.z.tgz")
  • or using the devtools R package (assuming you have C compiler installed):
install.packages("devtools") # Install devtools, if you haven't already.
devtools::install_github("DiceKriging", "DiceKrigingClub")

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Version

Install

install.packages('DiceKriging')

Monthly Downloads

9,763

Version

1.6.0

License

GPL-2 | GPL-3

Maintainer

Olivier Roustant

Last Published

February 23rd, 2021

Functions in DiceKriging (1.6.0)

camelback

2D test function
DiceKriging-package

Kriging Methods for Computer Experiments
covKernel-class

Class "covKernel"
checkNames

Consistency test between the column names of two matrices
SCAD

Penalty function
covTensorProduct-class

Class of tensor-product spatial covariances
covIso-class

Class of tensor-product spatial covariances with isotropic range
coef

Get coefficients values
covparam2vect

Auxiliary function
SCAD.derivative

Penalty function derivative
covVector.dx

Spatial covariance - Derivatives
kernelname

Get the kernel name
drop.response

Trend model formula operation
kmEstimate

Fitting Kriging Models
cv

Multiple fold cross validation for a km object
kmData

Fit and/or create kriging models
covUser-class

Class "covUser"
inputnames

Get the input variables names
show

Print values of a km object
covScaling-class

Class "covScaling"
covMatrixDerivative

Covariance matrix derivatives
hartman6

6D test function
branin

2D test function
covStruct.create

Spatial covariance - Class constructor
km

Fit and/or create kriging models
logLikFun

Concentrated log-likelihood of a km object
leaveOneOut.km

Leave-one-out for a km object
covParametersBounds

Boundaries for covariance parameters
km-class

Kriging models class
scalingFun1d

Scaling 1-dimensional function
nuggetflag

Get the nugget flag
ninput

Get the spatial dimension
logLikGrad

Concentrated log-Likelihood of a km object - Analytical gradient
simulate

Simulate GP values at any given set of points for a km object
scalingFun

Scaling function
predict

Predict values and confidence intervals at newdata for a km object
trend.deltax

Trend derivatives
leaveOneOutFun

Leave-one-out least square criterion of a km object
scalingGrad

Gradient of the dimensional Scaling function
trendMatrix.update

Trend model matrix operation
leaveOneOutGrad

Leave-one-out least square criterion - Analytical gradient
update

Update of a kriging model
logLik

log-likelihood of a km object
km1Nugget.init

Fitting Kriging Models
vect2covparam

Auxiliary function
covMatrix

Covariance matrix
covMat1Mat2

Cross covariance matrix
goldsteinPrice

2D test function
kmNuggets.init

Fitting Kriging Models
hartman3

3D test function
kmNoNugget.init

Fitting Kriging Models
nuggetvalue

Get or set the nugget value
plot

Diagnostic plot for the validation of a km object
computeAuxVariables

Auxiliary variables for kriging