DiceOptim: Kriging-Based Optimization for Computer Experiments

Efficient Global Optimization (EGO) algorithm and adaptations for parallel infill (multipoint EI), problems with noise, and problems with constraints.

Install the latest version of this package by entering the following in R:
AuthorV. Picheny, D. Ginsbourger, O. Roustant, with contributions by M. Binois, C. Chevalier, S. Marmin, and T. Wagner
Date of publication2016-09-15 17:33:46
MaintainerV. Picheny <victor.picheny@toulouse.inra.fr>
LicenseGPL-2 | GPL-3

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Man pages

AEI: Augmented Expected Improvement

AEI.grad: AEI's Gradient

AKG: Approximate Knowledge Gradient (AKG)

AKG.grad: AKG's Gradient

branin2: 2D test function

checkPredict: Prevention of numerical instability for a new observation

crit_AL: Expected Augmented Lagrangian Improvement

critcst_optimizer: Maximization of constrained Expected Improvement criteria

crit_EFI: Expected Feasible Improvement

crit_SUR_cst: Stepwise Uncertainty Reduction criterion

DiceOptim-package: Kriging-based optimization methods for computer experiments

easyEGO.cst: EGO algorithm with constraints

EGO.cst: Sequential constrained Expected Improvement maximization and...

EGO.nsteps: Sequential EI maximization and model re-estimation, with a...

EI: Analytical expression of the Expected Improvement criterion

EI.grad: Analytical gradient of the Expected Improvement criterion

EQI: Expected Quantile Improvement

EQI.grad: EQI's Gradient

fastfun: Fastfun function

fastfun-class: Class for fast to compute objective.

goldsteinprice: 2D test function

hartman4: 4D test function

integration_design_cst: Generic function to build integration points (for the SUR...

kriging.quantile: Kriging quantile

kriging.quantile.grad: Analytical gradient of the Kriging quantile of level beta

max_AEI: Maximizer of the Augmented Expected Improvement criterion...

max_AKG: Maximizer of the Expected Quantile Improvement criterion...

max_EI: Maximization of the Expected Improvement criterion

max_EQI: Maximizer of the Expected Quantile Improvement criterion...

max_qEI: Maximization of multipoint expected improvement criterion...

min_quantile: Minimization of the Kriging quantile.

noisy.optimizer: Optimization of homogenously noisy functions based on Kriging

ParrConstraint: 2D constraint function

qEGO.nsteps: Sequential multipoint Expected improvement (qEI)...

qEI: Analytical expression of the multipoint expected improvement...

qEI.grad: Gradient of the multipoint expected improvement (qEI)...

rosenbrock4: 4D test function

sampleFromEI: Sampling points according to the expected improvement...

sphere6: 6D sphere function

test_feas_vec: Test constraints violation (vectorized)

update_km_noisyEGO: Update of one or two Kriging models when adding new...


AEI Man page
AEI.grad Man page
AKG Man page
AKG.grad Man page
branin2 Man page
checkPredict Man page
crit_AL Man page
critcst_optimizer Man page
crit_EFI Man page
crit_SUR_cst Man page
DiceOptim Man page
DiceOptim-package Man page
easyEGO.cst Man page
EGO.cst Man page
EGO.nsteps Man page
EI Man page
EI.grad Man page
EQI Man page
EQI.grad Man page
fastfun Man page
fastfun-class Man page
goldsteinprice Man page
hartman4 Man page
integration_design_cst Man page
kriging.quantile Man page
kriging.quantile.grad Man page
max_AEI Man page
max_AKG Man page
max_EI Man page
max_EQI Man page
max_qEI Man page
min_quantile Man page
noisy.optimizer Man page
ParrConstraint Man page
predict,fastfun-method Man page
qEGO.nsteps Man page
qEI Man page
qEI.grad Man page
rosenbrock4 Man page
sampleFromEI Man page
simulate,fastfun-method Man page
sphere6 Man page
test_feas_vec Man page
update,fastfun-method Man page
update_km_noisyEGO Man page

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.