scalingGrad

Gradient of the Scaling function (marginal in dimension k) of Xiong et al. with respect to eta

models

Estimation, validation and prediction of kriging models. Important functions : km, print.km, plot.km, predict.km.

Olivier Roustant

DiceKriging

Kriging Methods for Computer Experiments

David Ginsbourger

Yves Deville

Clément Chevalier

Yann Richet

scalingGrad function

<dl> <dt>X</dt>
<dd>an n*d matrix standing for a design of n experiments in d-dimensional space.</dd> <dt>knots</dt>
<dd>a list of knots parametrizing the transformation.</dd> <dt>k</dt>
<dd>dimension of the input variables for which the gradient is calculated.</dd></dl>

Arguments

Gradient of the dimensional Scaling function — scalingGrad

<dl>

 <dt>X</dt>
<dd>an n*d matrix standing for a design of n experiments in d-dimensional space.</dd>

 <dt>knots</dt>
<dd>a list of knots parametrizing the transformation.</dd>

 <dt>k</dt>
<dd>dimension of the input variables for which the gradient is calculated.</dd>

</dl>

scalingGrad: Gradient of the dimensional Scaling function

Description

Usage

Value

Arguments

References

See Also