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.

1 | ```
affineScalingFun(X, knots, eta)
``` |

`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. |

The image of X by a scaling transformation of parameters knots and eta

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.

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