Evaluation of the "sur" criterion for a candidate point. To be used in optimization routines, like in max_sur. To avoid numerical instabilities, the new point is evaluated only if it is not too close to an existing observation, or if there is some observation noise. The criterion is the integral of the posterior sur uncertainty.
● Data Source:
CranContrib
● Keywords:
● Alias: sur_optim
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Function similar to the computeAuxVariables of the DiceKriging package, with a quicker implementation.
● Data Source:
CranContrib
● Keywords:
● Alias: computeAuxVariables_update
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fun_test2d_ranjan
(Package: KrigInv) :
2-dimensional test function "fun_test2d_ranjan"
(x1,x2) -> x1 + x2 + x1*x2
● Data Source:
CranContrib
● Keywords: internal
● Alias: fun_test2d_ranjan
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This function draws projections on various plans of a given measure of uncertainty. Possible measures are "pn" (probability of excursion) and measures specific to a sampling criterion: "sur", "timse" and "imse". This function can be used to print relevant outputs after having used the function EGI.
● Data Source:
CranContrib
● Keywords:
● Alias: print_uncertainty_nd
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jn_optim
(Package: KrigInv) :
jn criterion optimization
Evaluation of the "jn" criterion for a candidate point. To be used in the optimization routines max_sur with the argument real.volume.variance=TRUE. To avoid numerical instabilities, a new point is added to the design of experiments only if it is not too close to an existing observation, or if there is some observation noise. The criterion is the integral of the posterior expected jn uncertainty, which is the posterior expected variance of the excursion set's volume.
● Data Source:
CranContrib
● Keywords:
● Alias: jn_optim
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Evaluation of the parallel sur criterion for some candidate points. To be used in optimization routines, like in max_sur_parallel. To avoid numerical instabilities, the new points are evaluated only if they are not too close to an existing observation, or if there is some observation noise. The criterion is the integral of the posterior sur uncertainty.
● Data Source:
CranContrib
● Keywords:
● Alias: sur_optim_parallel
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Evaluation of the parallel timse criterion for some candidate points, assuming that some other points are also going to be evaluated. To be used in optimization routines, like in max_timse_parallel. To avoid numerical instabilities, the new points are evaluated only if they are not too close to an existing observation, or if there is some observation noise. The criterion is the integral of the posterior timse uncertainty.
● Data Source:
CranContrib
● Keywords:
● Alias: timse_optim_parallel2
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1 images
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fundet
(Package: KrigInv) :
1-dimensional test function "fundet"
sin(10*x)/(1+x)+2*cos(5*x)*x^3+0.841)/1.6
● Data Source:
CranContrib
● Keywords: internal
● Alias: fundet
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1 images
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This function draws the value of a given measure of uncertainty over the whole input domain (1D). Possible measures are "pn" (beeing the probability of excursion) and measures specific to a sampling criterion: "sur", "timse" and "imse". This function can be used to print relevant outputs after having used the function EGI.
● Data Source:
CranContrib
● Keywords:
● Alias: print_uncertainty_1d
●
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Computes or updates some auxiliary variables used for kriging (see below). This function is a copy of the computeAuxVariables function from the DiceKriging package, except that the calculation of the Cholesky decomposition is not performed, for cpu time savings.
● Data Source:
CranContrib
● Keywords: models
● Alias: computeAuxVariables_noChol
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providing 
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