kriging.quantile.grad
(Package: DiceOptim) :
Analytical gradient of the Kriging quantile of level beta
Computes the gradient of the Kriging quantile of level beta at the current location. Only available for Universal Kriging with constant trend (Ordinary Kriging).
● Data Source:
CranContrib
● Keywords: models, optimize
● Alias: kriging.quantile.grad
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EI.grad
(Package: DiceOptim) :
Analytical gradient of the Expected Improvement criterion
Computes the gradient of the Expected Improvement at the current location. The current minimum of the observations can be replaced by an arbitrary value (plugin), which is usefull in particular in noisy frameworks.
● Data Source:
CranContrib
● Keywords: models, optimize
● Alias: EI.grad
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Gradient of the Approximate Knowledge Gradient (AKG) criterion.
● Data Source:
CranContrib
● Keywords:
● Alias: AKG.grad
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Analytical gradient of the Expected Quantile Improvement (EQI) criterion.
● Data Source:
CranContrib
● Keywords:
● Alias: EQI.grad
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max_AEI
(Package: DiceOptim) :
Maximizer of the Augmented Expected Improvement criterion function
Maximization, based on the package rgenoud of the Augmented Expected Improvement (AEI) criterion.
● Data Source:
CranContrib
● Keywords:
● Alias: max_AEI
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EGO.nsteps
(Package: DiceOptim) :
Sequential EI maximization and model re-estimation, with a number of iterations fixed in advance by the user
Executes nsteps iterations of the EGO method to an object of class km. At each step, a kriging model is re-estimated (including covariance parameters re-estimation) based on the initial design points plus the points visited during all previous iterations; then a new point is obtained by maximizing the Expected Improvement criterion (EI).
● Data Source:
CranContrib
● Keywords: optimize
● Alias: EGO.nsteps
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1 images
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Goldstein-Price 2-dimensional test function.
● Data Source:
CranContrib
● Keywords: internal, optimize
● Alias: goldsteinprice
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max_EI
(Package: DiceOptim) :
Maximization of the Expected Improvement criterion
Given an object of class km and a set of tuning parameters (lower,upper,parinit, and control), max_EI performs the maximization of the Expected Improvement criterion and delivers the next point to be visited in an EGO-like procedure.
● Data Source:
CranContrib
● Keywords: optimize
● Alias: max_EI
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1 images
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AKG
(Package: DiceOptim) :
Approximate Knowledge Gradient (AKG)
Evaluation of the Approximate Knowledge Gradient (AKG) criterion.
● Data Source:
CranContrib
● Keywords:
● Alias: AKG
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4 images
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Evaluation of a kriging quantile a a new point. To be used in an optimization loop.
● Data Source:
CranContrib
● Keywords:
● Alias: kriging.quantile
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4 images
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providing 
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