edm_crit: Distance in measure criterion

Description Usage Arguments Value References

Description

Computes the distance in measure criterion.

Usage

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edm_crit(x, integration.points, integration.weights = NULL,
  intpoints.oldmean, intpoints.oldsd, precalc.data, model, threshold,
  batchsize, alpha, current.crit)

Arguments

x

vector of dimension d representing the ith point where to compute the criterion

integration.points

p*d matrix of points for numerical integration in the X space.

integration.weights

Vector of size p corresponding to the weights of these integration points.

intpoints.oldmean

Vector of size p corresponding to the kriging mean at the integration points.

intpoints.oldsd

Vector of size p corresponding to the kriging standard deviation at the integration points.

precalc.data

list result of precomputeUpdateData with model and x.

model

km model

threshold

threshold selected for excursion set

batchsize

number of simulation points

alpha

value of Vorob'ev threshold

current.crit

Current value of the criterion

Value

the value of the expected distance in measure criterion at x

References

Azzimonti D. F., Bect J., Chevalier C. and Ginsbourger D. (2016). Quantifying uncertainties on excursion sets under a Gaussian random field prior. SIAM/ASA Journal on Uncertainty Quantification, 4(1):850–874.

Azzimonti, D. (2016). Contributions to Bayesian set estimation relying on random field priors. PhD thesis, University of Bern.


pGPx documentation built on May 2, 2019, 3:28 a.m.