Package: KrigInv 1.4.2

KrigInv: Kriging-Based Inversion for Deterministic and Noisy Computer Experiments

Criteria and algorithms for sequentially estimating level sets of a multivariate numerical function, possibly observed with noise.

Authors:Clement Chevalier [aut], Dario Azzimonti [aut, cre], David Ginsbourger [aut], Victor Picheny [aut], Yann Richet [ctb]

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KrigInv.pdf |KrigInv.html✨
KrigInv/json (API)

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

Peer review:

On CRAN:

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

2.83 score 4 packages 54 scripts 1.0k downloads 33 exports 9 dependencies

Last updated 2 years agofrom:82245e992f. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 15 2024
R-4.5-winNOTENov 15 2024
R-4.5-linuxNOTENov 15 2024
R-4.4-winNOTENov 15 2024
R-4.4-macNOTENov 15 2024
R-4.3-winOKNov 15 2024
R-4.3-macOKNov 15 2024

Exports:bichon_optimcomputeQuickKrigcovcomputeRealVolumeConstantEGIEGIparallelexcursion_probabilityintegration_designjn_optim_paralleljn_optim_parallel2max_futureVol_parallelmax_infill_criterionmax_sur_parallelmax_timse_parallelmax_vorob_parallelprecomputeUpdateDatapredict_nobias_kmpredict_update_km_parallelprint_uncertaintyprint_uncertainty_1dprint_uncertainty_2dprint_uncertainty_ndranjan_optimsur_optim_parallelsur_optim_parallel2timse_optim_paralleltimse_optim_parallel2tmse_optimtsee_optimvorob_optim_parallelvorob_optim_parallel2vorob_thresholdvorobVol_optim_parallelvorobVol_optim_parallel2

Dependencies:anMCDiceKrigingmvtnormpbivnormrandtoolboxRcppRcppArmadillorgenoudrngWELL

Readme and manuals

Help Manual

Help pageTopics
Kriging-Based Inversion for Deterministic and Noisy Computer ExperimentsKrigInv
Bichon et al.'s Expected Feasibility criterionbichon_optim
Quick computation of kriging covariancescomputeQuickKrigcov
A constant used to calculate the expected excursion set's volume variancecomputeRealVolumeConstant
Efficient Global Inversion: sequential inversion algorithm based on Kriging.EGI
Efficient Global Inversion: parallel version to get batchsize locations at each iterationEGIparallel
Excursion probability with one or many thresholdsexcursion_probability
Construction of a sample of integration points and weightsintegration_design
Parallel jn criterionjn_optim_parallel
Parallel jn criterionjn_optim_parallel2
Maximize parallel volume criterionmax_futureVol_parallel
Optimizer for the infill criteriamax_infill_criterion
Minimizer of the parallel '"sur"' or '"jn"' criterionmax_sur_parallel
Minimizer of the parallel timse criterionmax_timse_parallel
Minimizer of the parallel vorob criterionmax_vorob_parallel
Useful precomputations to quickly update kriging mean and varianceprecomputeUpdateData
Kriging predictionspredict_nobias_km
Quick update of kriging means and variances when one or many new points are added to the DOE.predict_update_km_parallel
Prints a measure of uncertainty for a function of any dimension.print_uncertainty
Prints a measure of uncertainty for 1d function.print_uncertainty_1d
Prints a measure of uncertainty for 2d function.print_uncertainty_2d
Print a measure of uncertainty for functions with dimension d strictly larger than 2.print_uncertainty_nd
Ranjan et al.'s Expected Improvement criterionranjan_optim
Parallel sur criterionsur_optim_parallel
Parallel sur criterionsur_optim_parallel2
Parallel targeted IMSE criteriontimse_optim_parallel
Parallel timse criteriontimse_optim_parallel2
Targeted MSE criteriontmse_optim
Two Sided Expected Exceedance criteriontsee_optim
Parallel Vorob'ev criterionvorob_optim_parallel
Parallel Vorob'ev criterionvorob_optim_parallel2
Calculation of the Vorob'ev thresholdvorob_threshold
Compute volume criterionvorobVol_optim_parallel
Compute volume criterionvorobVol_optim_parallel2