RDocumentation
Moon
Search all packages and functions
Readme not available 😞
Copy Link
Copy
Link to current version
Version
Version
2.1.1
2.1.0
2.0.1
2.0
1.5
1.4
1.3.3
1.3.2
1.3.1
1.2.1
1.0
Down Chevron
Install
install.packages('DiceOptim')
Monthly Downloads
2,415
Version
2.1.1
License
GPL-2 | GPL-3
Maintainer
V. Picheny
Last Published
February 2nd, 2021
Functions in DiceOptim (2.1.1)
Search functions
EQI
Expected Quantile Improvement
AEI.grad
AEI's Gradient
AKG
Approximate Knowledge Gradient (AKG)
AEI
Augmented Expected Improvement
AKG.grad
AKG's Gradient
DiceOptim-package
Kriging-based optimization methods for computer experiments
EGO.cst
Sequential constrained Expected Improvement maximization and model re-estimation, with a number of iterations fixed in advance by the user
EI
Analytical expression of the Expected Improvement criterion
EGO.nsteps
Sequential EI maximization and model re-estimation, with a number of iterations fixed in advance by the user
EI.grad
Analytical gradient of the Expected Improvement criterion
EQI.grad
EQI's Gradient
checkPredict
Prevention of numerical instability for a new observation
fastfun-class
Class for fast to compute objective.
ParrConstraint
2D constraint function
fastfun
Fastfun function
kriging.quantile.grad
Analytical gradient of the Kriging quantile of level beta
max_AEI
Maximizer of the Augmented Expected Improvement criterion function
critcst_optimizer
Maximization of constrained Expected Improvement criteria
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.
integration_design_cst
Generic function to build integration points (for the SUR criterion)
kriging.quantile
Kriging quantile
crit_AL
Expected Augmented Lagrangian Improvement
goldsteinprice
2D test function
update_km_noisyEGO
Update of one or two Kriging models when adding new observation
max_AKG
Maximizer of the Expected Quantile Improvement criterion function
TREGO.nsteps
Trust-region based EGO algorithm.
hartman4
4D test function
easyEGO.cst
EGO algorithm with constraints
max_EI
Maximization of the Expected Improvement criterion
branin2
2D test function
qEI
Analytical expression of the multipoint expected improvement (qEI) criterion
test_feas_vec
Test constraints violation (vectorized)
max_EQI
Maximizer of the Expected Quantile Improvement criterion function
max_crit
Maximization of the Expected Improvement criterion
qEI.grad
Gradient of the multipoint expected improvement (qEI) criterion
crit_EFI
Expected Feasible Improvement
crit_SUR_cst
Stepwise Uncertainty Reduction criterion
noisy.optimizer
Optimization of homogenously noisy functions based on Kriging
sphere6
6D sphere function
qEGO.nsteps
Sequential multipoint Expected improvement (qEI) maximizations and model re-estimation
fastEGO.nsteps
Sequential EI maximization and model re-estimation, with a number of iterations fixed in advance by the user
max_qEI
Maximization of multipoint expected improvement criterion (qEI)
min_quantile
Minimization of the Kriging quantile.
rosenbrock4
4D test function
sampleFromEI
Sampling points according to the expected improvement criterion