mean_Delta_T

a matrix \(r x d\) containing the \(r\) points where the function is to be computed.

the <a rd-options="DiceKriging" href="/link/km?package=profExtrema&version=0.2.1&to=DiceKriging" data-mini-rdoc="DiceKriging::km">km</a> model of the Gaussian process \(Z\).

kmModel

the matrix \(l x d\) containing the pilot points \(G\).

simupoints

the upper triangular factor of the Choleski decomposition of the covariance matrix of <code>rbind(kmModel@X,simupoints)</code>

T.mat

the evaluation of the trend function at <code>rbind(kmModel@X,simupoints)</code>, see <a rd-options="stats" href="/link/model.matrix?package=profExtrema&version=0.2.1&to=stats" data-mini-rdoc="stats::model.matrix">model.matrix</a>.

F.mat

The function mean_Delta_T computes the mean function of the difference process \(Z_x - \widetilde{Z}_x\) at <code>x</code>.

Computes profile extrema functions for arbitrary functions. If the function is expensive-to-evaluate it computes profile extrema by emulating the function with a Gaussian process (using package 'DiceKriging'). In this case uncertainty quantification on the profile extrema can also be computed. The different plotting functions for profile extrema give the user a tool to better locate excursion sets.

Dario Azzimonti

profExtrema

Compute and Visualize Profile Extrema Functions

mean_Delta_T function

the <a rd-options='DiceKriging' href='km'>km</a> model of the Gaussian process \(Z\).

the evaluation of the trend function at <code>rbind(kmModel@X,simupoints)</code>, see <a rd-options='stats' href='model.matrix'>model.matrix</a>.

mean_Delta_T: mean function of difference process

Description

Usage

Arguments

Value