Apply the trained cubic, MQ or Gaussian RBF interpolation to new data for d>1.
interpRBF(x, rbf.model)vector holding a point of dimension d
trained RBF model (or set of models), see trainCubicRBF
or trainGaussRBF
value \(s(\vec{x})\) of the trained model at \(\vec{x}\) - or - vector \(s_j( \vec{x})\) with values for all trained models \(j=1,...,m\) at \(\vec{x}\)