Package: KrigInv 1.4.3

Dario Azzimonti

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. The methods are described in Chevalier, Picheny and Ginsbourger (2014) <doi:10.1016/j.csda.2013.03.008> and Azzimonti, Ginsbourger, Chevalier, Bect and Richet (2021) <doi:10.1080/00401706.2019.1693427>.

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

KrigInv_1.4.3.tar.gz
KrigInv_1.4.3.zip(r-4.7-any)KrigInv_1.4.3.zip(r-4.6-any)KrigInv_1.4.3.zip(r-4.5-any)
KrigInv_1.4.3.tgz(r-4.6-any)KrigInv_1.4.3.tgz(r-4.5-any)
KrigInv_1.4.3.tar.gz(r-4.7-any)KrigInv_1.4.3.tar.gz(r-4.6-any)
KrigInv_1.4.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
KrigInv/json (API)

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

Bug tracker:https://github.com/kriginvteam/kriginv/issues

On CRAN:

Conda:

5.45 score 1 stars 5 packages 59 scripts 2.1k downloads 33 exports 9 dependencies

Last updated from:88a8e80a2e. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK125
source / vignettesOK191
linux-releaseOK114
macos-releaseOK180
macos-oldrelOK217
windows-develOK177
windows-releaseOK197
windows-oldrelOK170
wasm-releaseOK81

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-package KrigInv
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 KrigingEGI
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 DOEpredict_update_km_parallel
Prints a measure of uncertainty for a function of any dimensionprint_uncertainty
Prints a measure of uncertainty for 1d functionprint_uncertainty_1d
Prints a measure of uncertainty for 2d functionprint_uncertainty_2d
Print a measure of uncertainty for functions with dimension d strictly larger than 2print_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