affineScalingFun: Scaling function (affine case)
In IRSN/DiceKriging: Kriging Methods for Computer Experiments
Description
Usage
Arguments
Value
References
See Also
Description
Parametric transformation of the input space variables. The transformation is obtained coordinatewise by integrating piecewise affine marginal "densities" parametrized by a vector of knots and a matrix of density values at the knots. See references for more detail.
Usage
1
affineScalingFun(X, knots, eta)
Arguments
X
an n*d matrix standing for a design of n experiments in d-dimensional space
knots
a (K+1) vector of knots parametrizing the transformation. The knots are here the same in all dimensions.
eta
a d*(K+1) matrix of coefficients parametrizing the d marginal transformations. Each line stands for a set of (K+1) marginal density values at the knots defined above.
Value
The image of X by a scaling transformation of parameters knots and eta
References
Y. Xiong, W. Chen, D. Apley, and X. Ding (2007), Int. J. Numer. Meth. Engng, A non-stationary covariance-based Kriging method for metamodelling in engineering design.
See Also
IRSN/DiceKriging documentation built on May 8, 2019, 1:25 p.m.
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Description Usage Arguments Value References See Also
Description
Parametric transformation of the input space variables. The transformation is obtained coordinatewise by integrating piecewise affine marginal "densities" parametrized by a vector of knots and a matrix of density values at the knots. See references for more detail.
Usage
1 | affineScalingFun(X, knots, eta)
|
Arguments
X |
an n*d matrix standing for a design of n experiments in d-dimensional space |
knots |
a (K+1) vector of knots parametrizing the transformation. The knots are here the same in all dimensions. |
eta |
a d*(K+1) matrix of coefficients parametrizing the d marginal transformations. Each line stands for a set of (K+1) marginal density values at the knots defined above. |
Value
The image of X by a scaling transformation of parameters knots and eta
References
Y. Xiong, W. Chen, D. Apley, and X. Ding (2007), Int. J. Numer. Meth. Engng, A non-stationary covariance-based Kriging method for metamodelling in engineering design.
See Also
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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