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 |