Package: rlibkriging 0.9-0

rlibkriging: Kriging Models using the 'libKriging' Library

Interface to 'libKriging' 'C++' library <https://github.com/libKriging> that should provide most standard Kriging / Gaussian process regression features (like in 'DiceKriging', 'kergp' or 'RobustGaSP' packages). 'libKriging' relies on Armadillo linear algebra library (Apache 2 license) by Conrad Sanderson, 'lbfgsb_cpp' is a 'C++' port around 'lbfgsb' library (BSD-3 license) by Ciyou Zhu, Richard Byrd, Jorge Nocedal and Jose Luis Morales used for hyperparameters optimization.

Authors:Yann Richet [aut, cre], Pascal Havé [aut], Yves Deville [aut], Conrad Sanderson [ctb], Ciyou Zhu [ctb], Richard Byrd [ctb], Jorge Nocedal [ctb], Jose Luis Morales [ctb], Mike Smith [ctb]

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rlibkriging/json (API)

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

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • arpack– Fortran77 subroutines to solve large scale eigenvalue problems
  • c++– GNU Standard C++ Library v3

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.02 score 105 scripts 195 downloads 26 exports 3 dependencies

Last updated 3 months agofrom:6f73650540. Checks:OK: 1 NOTE: 5 WARNING: 3. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 24 2024
R-4.5-win-x86_64WARNINGAug 24 2024
R-4.5-linux-x86_64NOTEAug 24 2024
R-4.4-win-x86_64WARNINGAug 24 2024
R-4.4-mac-x86_64NOTEAug 24 2024
R-4.4-mac-aarch64NOTEAug 24 2024
R-4.3-win-x86_64WARNINGAug 24 2024
R-4.3-mac-x86_64NOTEAug 24 2024
R-4.3-mac-aarch64NOTEAug 24 2024

Exports:as.kmcopycovMatfitKMKrigingleaveOneOutleaveOneOutFunleaveOneOutVecloadload.Krigingload.NoiseKrigingload.NuggetKriginglogLikelihoodlogLikelihoodFunlogMargPostlogMargPostFunNoiseKMNoiseKrigingNuggetKMNuggetKrigingpredictsavesimulateupdateupdate_simulate

Dependencies:DiceKrigingRcppRcppArmadillo

Readme and manuals

Help Manual

Help pageTopics
Coerce an Object into a 'km' Objectas.km
Coerce a 'Kriging' object into the '"km"' class of the 'DiceKriging' package.as.km,Kriging,Kriging-method as.km.Kriging
Coerce a 'NoiseKriging' object into the '"km"' class of the 'DiceKriging' package.as.km,NoiseKriging,NoiseKriging-method as.km.NoiseKriging
Coerce a 'NuggetKriging' object into the '"km"' class of the 'DiceKriging' package.as.km.NuggetKriging
Coerce a 'Kriging' Object into a Listas.list,Kriging,Kriging-method as.list.Kriging
Coerce a 'NoiseKriging' Object into a Listas.list,NoiseKriging,NoiseKriging-method as.list.NoiseKriging
Coerce a 'NuggetKriging' Object into a Listas.list,NuggetKriging,NuggetKriging-method as.list.NuggetKriging
Shortcut to provide functions to the S3 class "Kriging"classKriging
Shortcut to provide functions to the S3 class "NoiseKriging"classNoiseKriging
Shortcut to provide functions to the S3 class "NuggetKriging"classNuggetKriging
Duplicate object.copy
Duplicate a Kriging Modelcopy,Kriging,Kriging-method copy.Kriging
Duplicate a NoiseKriging Modelcopy,NoiseKriging,NoiseKriging-method copy.NoiseKriging
Duplicate a NuggetKriging Modelcopy,NuggetKriging,NuggetKriging-method copy.NuggetKriging
covariance functioncovMat
Compute Covariance Matrix of Kriging ModelcovMat,Kriging,Kriging-method covMat.Kriging
Compute Covariance Matrix of NoiseKriging ModelcovMat,NoiseKriging,NoiseKriging-method covMat.NoiseKriging
Compute Covariance Matrix of NuggetKriging ModelcovMat,NuggetKriging,NuggetKriging-method covMat.NuggetKriging
Fit model on data.fit
Fit 'Kriging' object on given data.fit.Kriging
Fit 'NoiseKriging' object on given data.fit.NoiseKriging
Fit 'NuggetKriging' object on given data.fit.NuggetKriging
Create an 'KM' ObjectKM
S4 class for Kriging Models Extending the '"km"' ClassKM-class
Create an object with S3 class '"Kriging"' using the 'libKriging' library.Kriging
Compute Leave-One-OutleaveOneOut
Get leaveOneOut of Kriging ModelleaveOneOut,Kriging,Kriging-method leaveOneOut.Kriging
Leave-One-Out functionleaveOneOutFun
Compute Leave-One-Out (LOO) error for an object with S3 class '"Kriging"' representing a kriging model.leaveOneOutFun,Kriging,Kriging-method leaveOneOutFun.Kriging
Leave-One-Out vectorleaveOneOutVec
Compute Leave-One-Out (LOO) vector error for an object with S3 class '"Kriging"' representing a kriging model.leaveOneOutVec,Kriging,Kriging-method leaveOneOutVec.Kriging
Load any Kriging Model from a file storage.load
Load a Kriging Model from a file storageload.Kriging
Load a NoiseKriging Model from a file storageload.NoiseKriging
Load a NuggetKriging Model from a file storageload.NuggetKriging
Compute Log-LikelihoodlogLikelihood
Get Log-Likelihood of Kriging ModellogLikelihood,Kriging,Kriging-method logLikelihood.Kriging
Get logLikelihood of NoiseKriging ModellogLikelihood,NoiseKriging,NoiseKriging-method logLikelihood.NoiseKriging
Get logLikelihood of NuggetKriging ModellogLikelihood,NuggetKriging,NuggetKriging-method logLikelihood.NuggetKriging
Log-Likelihood functionlogLikelihoodFun
Compute Log-Likelihood of Kriging ModellogLikelihoodFun,Kriging,Kriging-method logLikelihoodFun.Kriging
Compute Log-Likelihood of NoiseKriging ModellogLikelihoodFun,NoiseKriging,NoiseKriging-method logLikelihoodFun.NoiseKriging
Compute Log-Likelihood of NuggetKriging ModellogLikelihoodFun,NuggetKriging,NuggetKriging-method logLikelihoodFun.NuggetKriging
Compute log-Marginal PosteriorlogMargPost
Get logMargPost of Kriging ModellogMargPost,Kriging,Kriging-method logMargPost.Kriging
Get logMargPost of NuggetKriging ModellogMargPost,NuggetKriging,NuggetKriging-method logMargPost.NuggetKriging
log-Marginal Posterior functionlogMargPostFun
Compute the log-marginal posterior of a kriging model, using the prior XXXY.logMargPostFun,Kriging,Kriging-method logMargPostFun.Kriging
Compute the log-marginal posterior of a kriging model, using the prior XXXY.logMargPostFun,NuggetKriging,NuggetKriging-method logMargPostFun.NuggetKriging
Create an 'NoiseKM' ObjectNoiseKM
S4 class for NoiseKriging Models Extending the '"km"' ClassNoiseKM-class
Create an object with S3 class '"NoiseKriging"' using the 'libKriging' library.NoiseKriging
Create an 'NuggetKM' ObjectNuggetKM
S4 class for NuggetKriging Models Extending the '"km"' ClassNuggetKM-class
Create an object with S3 class '"NuggetKriging"' using the 'libKriging' library.NuggetKriging
Prediction Method for a 'KM' Objectpredict,KM-method
Prediction Method for a 'NoiseKM' Objectpredict,NoiseKM-method
Prediction Method for a 'NuggetKM' Objectpredict,NuggetKM-method
Predict from a 'Kriging' object.predict.Kriging
Predict from a 'NoiseKriging' object.predict.NoiseKriging
Predict from a 'NuggetKriging' object.predict.NuggetKriging
Print the content of a 'Kriging' object.print.Kriging
Print the content of a 'NoiseKriging' object.print.NoiseKriging
Print the content of a 'NuggetKriging' object.print.NuggetKriging
Save object.save
Save a Kriging Model to a file storagesave,Kriging,Kriging-method save.Kriging
Save a NoiseKriging Model to a file storagesave,NoiseKriging,NoiseKriging-method save.NoiseKriging
Save a NuggetKriging Model to a file storagesave,NuggetKriging,NuggetKriging-method save.NuggetKriging
Simulation from a 'KM' Objectsimulate,KM-method
Simulation from a 'NoiseKM' Objectsimulate,NoiseKM-method
Simulation from a 'NuggetKM' Objectsimulate,NuggetKM-method
Simulation from a 'Kriging' model object.simulate.Kriging
Simulation from a 'NoiseKriging' model object.simulate.NoiseKriging
Simulation from a 'NuggetKriging' model object.simulate.NuggetKriging
Update simulation of model on data.update_simulate
Update previous simulation of a 'Kriging' model object.update_simulate.Kriging
Update previous simulation of a 'NoiseKriging' model object.update_simulate.NoiseKriging
Update previous simulation of a 'NuggetKriging' model object.update_simulate.NuggetKriging
Update a 'KM' Object with New Pointsupdate,KM-method
Update a 'NoiseKM' Object with New Pointsupdate,NoiseKM-method
Update a 'NuggetKM' Object with New Pointsupdate,NuggetKM-method
Update a 'Kriging' model object with new pointsupdate.Kriging
Update a 'NoiseKriging' model object with new pointsupdate.NoiseKriging
Update a 'NuggetKriging' model object with new pointsupdate.NuggetKriging