Package: DiceKriging 1.6.0

DiceKriging: Kriging Methods for Computer Experiments

Estimation, validation and prediction of kriging models. Important functions : km, print.km, plot.km, predict.km.

Authors:Olivier Roustant, David Ginsbourger, Yves Deville. Contributors: Clement Chevalier, Yann Richet.

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DiceKriging.pdf |DiceKriging.html
DiceKriging/json (API)

# Install 'DiceKriging' in R:
install.packages('DiceKriging', repos = c('https://roustant.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/dicekrigingclub/www/issues

On CRAN:

6.94 score 4 stars 33 packages 486 scripts 9.1k downloads 1 mentions 52 exports 0 dependencies

Last updated 4 years agofrom:547135515e. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 01 2024
R-4.5-win-x86_64OKNov 01 2024
R-4.5-linux-x86_64OKNov 01 2024
R-4.4-win-x86_64OKNov 01 2024
R-4.4-mac-x86_64OKNov 01 2024
R-4.4-mac-aarch64OKNov 01 2024
R-4.3-win-x86_64OKNov 01 2024
R-4.3-mac-x86_64OKNov 01 2024
R-4.3-mac-aarch64OKNov 01 2024

Exports:branincamelbackcheckNamescheckNamesListcoefcomputeAuxVariablescovMat1Mat2covMatrixcovMatrixDerivativecovparam2vectcovParametersBoundscovStruct.createcovVector.dxcvdrop.responsegoldsteinPricehartman3hartman6inputnameskernelnamekmkm1Nugget.initkmDatakmEstimatekmNoNugget.initkmNuggets.initleaveOneOut.kmleaveOneOutFunleaveOneOutGradlogLik.kmlogLikFunlogLikGradninputnuggetflagnuggetvaluenuggetvalue<-plotplot.kmpredictpredict.kmSCADSCAD.derivativescalingFunscalingFun1dscalingGradshowsimulatesummarytrend.deltaxtrendMatrix.updateupdatevect2covparam

Dependencies:

Readme and manuals

Help Manual

Help pageTopics
Kriging Methods for Computer ExperimentsDiceKriging
Consistency test between the column names of two matricescheckNames checkNamesList
Get coefficients valuescoef
Auxiliary variables for krigingcomputeAuxVariables
Class of tensor-product spatial covariances with isotropic rangecoef,covIso-method covIso-class covMat1Mat2,covIso-method covMatrix,covIso-method covMatrixDerivative,covIso-method covparam2vect,covIso-method covParametersBounds,covIso-method covVector.dx,covIso-method inputnames,covIso-method kernelname,covIso-method ninput,covIso-method nuggetflag,covIso-method nuggetvalue,covIso-method nuggetvalue<-,covIso,numeric-method show,covIso-method summary,covIso-method vect2covparam,covIso-method
Class "covKernel"covKernel-class
Cross covariance matrixcovMat1Mat2
Covariance matrixcovMatrix
Boundaries for covariance parameterscovParametersBounds
Class "covScaling"coef,covScaling-method covMat1Mat2,covScaling-method covMatrix,covScaling-method covMatrixDerivative,covScaling-method covparam2vect,covScaling-method covParametersBounds,covScaling-method covScaling-class covVector.dx,covScaling-method inputnames,covScaling-method kernelname,covScaling-method ninput,covScaling-method nuggetflag,covScaling-method nuggetvalue,covScaling-method nuggetvalue<-,covScaling,numeric-method show,covScaling-method summary,covScaling-method vect2covparam,covScaling-method
Class of tensor-product spatial covariancescoef,covTensorProduct-method covMat1Mat2,covTensorProduct-method covMatrix,covTensorProduct-method covMatrixDerivative,covTensorProduct-method covparam2vect,covTensorProduct-method covParametersBounds,covTensorProduct-method covTensorProduct-class covVector.dx,covTensorProduct-method inputnames,covTensorProduct-method kernelname,covTensorProduct-method ninput,covTensorProduct-method nuggetflag,covTensorProduct-method nuggetvalue,covTensorProduct-method nuggetvalue<-,covTensorProduct,numeric-method show,covTensorProduct-method summary,covTensorProduct-method vect2covparam,covTensorProduct-method
Class "covUser"coef,covUser-method covMat1Mat2,covUser-method covMatrix,covUser-method covUser-class nuggetflag,covUser-method nuggetvalue,covUser-method nuggetvalue<-,covUser,numeric-method show,covUser-method
Multiple fold cross validation for a km objectcv
Get the input variables namesinputnames
Get the kernel namekernelname
Fit and/or create kriging modelskm
Kriging models classcoef,km-method km-class
Fit and/or create kriging modelskmData
Leave-one-out for a km objectleaveOneOut.km
Leave-one-out least square criterion of a km objectleaveOneOutFun
Leave-one-out least square criterion - Analytical gradientleaveOneOutGrad
log-likelihood of a km objectlogLik logLik,km-method logLik.km
Concentrated log-likelihood of a km objectlogLikFun
Get the spatial dimensionninput
Get the nugget flagnuggetflag
Get or set the nugget valuenuggetvalue nuggetvalue<-
Diagnostic plot for the validation of a km objectplot plot,km-method plot.km
Predict values and confidence intervals at newdata for a km objectpredict predict,km-method predict.km
Penalty functionSCAD
Scaling functionscalingFun
Scaling 1-dimensional functionscalingFun1d
Gradient of the dimensional Scaling functionscalingGrad
Print values of a km objectshow,km-method
Simulate GP values at any given set of points for a km objectsimulate simulate,km-method
Update of a kriging modelupdate update,km-method update.km