R: Kriging-Based Optimization for Computer Experiments

# Kriging-Based Optimization for Computer Experiments

## Documentation for package ‘DiceOptim’ version 2.1.1

- DESCRIPTION file.

## Help Pages

DiceOptim-package | Kriging-based optimization methods for computer experiments
AEI | Augmented Expected Improvement
AEI.grad | AEI's Gradient
AKG | Approximate Knowledge Gradient (AKG)
AKG.grad | AKG's Gradient
checkPredict | Prevention of numerical instability for a new observation
critcst_optimizer | Maximization of constrained Expected Improvement criteria
crit_AL | Expected Augmented Lagrangian Improvement
crit_EFI | Expected Feasible Improvement
crit_SUR_cst | Stepwise Uncertainty Reduction criterion
DiceOptim | Kriging-based optimization methods for computer experiments
easyEGO | User-friendly wrapper of the functions 'fastEGO.nsteps' and 'TREGO.nsteps'. Generates initial DOEs and kriging models (objects of class 'km'), and executes 'nsteps' iterations of either EGO or TREGO.
easyEGO.cst | EGO algorithm with constraints
EGO.cst | Sequential constrained Expected Improvement maximization and model re-estimation, with a number of iterations fixed in advance by the user
EGO.nsteps | Sequential EI maximization and model re-estimation, with a number of iterations fixed in advance by the user
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
fastEGO.nsteps | Sequential EI maximization and model re-estimation, with a number of iterations fixed in advance by the user
fastfun | Fastfun function
integration_design_cst | Generic function to build integration points (for the SUR criterion)
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 function
max_AKG | Maximizer of the Expected Quantile Improvement criterion function
max_crit | Maximization of the Expected Improvement criterion
max_EI | Maximization of the Expected Improvement criterion
max_EQI | Maximizer of the Expected Quantile Improvement criterion function
max_qEI | Maximization of multipoint expected improvement criterion (qEI)
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) maximizations and model re-estimation
qEI | Analytical expression of the multipoint expected improvement (qEI) criterion
qEI.grad | Gradient of the multipoint expected improvement (qEI) criterion
sampleFromEI | Sampling points according to the expected improvement criterion
test_feas_vec | Test constraints violation (vectorized)
TREGO.nsteps | Trust-region based EGO algorithm.
update_km_noisyEGO | Update of one or two Kriging models when adding new observation