GParetoptim
(Package: GPareto) :
Sequential multi-objective Expected Improvement maximization and model re-estimation,
Executes nsteps iterations of multi-objective EGO methods to objects of class km. At each step, kriging models are 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 one of the four multi-objective Expected Improvement criteria available.
● Data Source:
CranContrib
● Keywords:
● Alias: GParetoptim
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plotGPareto
(Package: GPareto) :
Plot multi-objective optimization results and post-processing
Display results of multi-objective optimization returned by either GParetoptim or easyGParetoptim, possibly completed with various post-processings of uncertainty quantification.
● Data Source:
CranContrib
● Keywords:
● Alias: plotGPareto
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plotSymDifRNP
(Package: GPareto) :
Symmetrical difference of RNP sets
Plot the symmetrical difference between two Random Non-Dominated Point (RNP) sets.
● Data Source:
CranContrib
● Keywords:
● Alias: plotSymDifRNP
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1 images
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crit_SUR
(Package: GPareto) :
Analytical expression of the SUR criterion for two or three objectives.
Computes the SUR criterion (Expected Excursion Volume Reduction) at point x for 2 or 3 objectives. To avoid numerical instabilities, the new point is penalized if it is too close to an existing observation.
● Data Source:
CranContrib
● Keywords:
● Alias: crit_SUR
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Displays the probability of non-domination in the variable space. In dimension larger than two, projections in 2D subspaces are displayed.
● Data Source:
CranContrib
● Keywords:
● Alias: plot_uncertainty
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getDesign
(Package: GPareto) :
Get design corresponding to an objective target
Find the design that maximizes the probability of dominating a target given by the user.
● Data Source:
CranContrib
● Keywords:
● Alias: getDesign
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plotParetoEmp
(Package: GPareto) :
Pareto front visualization
Plot the Pareto front with step functions.
● Data Source:
CranContrib
● Keywords:
● Alias: plotParetoEmp
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2 images
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fastfun-class
(Package: GPareto) :
Class for fast to compute objective.
Class for fast to compute objective.
● Data Source:
CranContrib
● Keywords: internal
● Alias: fastfun-class, predict,fastfun-method, simulate,fastfun-method, update,fastfun-method
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ZDT1
(Package: GPareto) :
Test functions of x
Multi-objective test functions.
● Data Source:
CranContrib
● Keywords:
● Alias: DTLZ1, DTLZ2, DTLZ3, DTLZ7, MOP2, MOP3, P1, P2, ZDT1, ZDT2, ZDT3, ZDT4, ZDT6
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8 images
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CPF
(Package: GPareto) :
Conditional Pareto Front simulations
Compute (on a regular grid) the empirical attainment function from conditional simulations of Gaussian processes corresponding to two objectives. This is used to estimate the Vorob'ev expectation of the attained set and the Vorob'ev deviation.
● Data Source:
CranContrib
● Keywords:
● Alias: CPF
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1 images
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