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I have a N-dimensional dataset, for which I need to apply multivariate interpolation. Is there a possible way to use different kind of interpolation methods in different dimensions? I considered to do this since I want to reduce the overall interpolation error, by choosing the interpolation type for each dimension. So far I only found methods which use a single interpolation type (e.g. cubic spline, linear,...) for all dimensions (such as the Matlab function interpn or the Scipy libary, ...). I'm already very thankful for a reference to literature, as I couldn't find anything.

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  • $\begingroup$ First, have a look at en.wikipedia.org/wiki/Multivariate_interpolation $\endgroup$ – Claude Leibovici Feb 10 at 9:24
  • $\begingroup$ Thank you. However, this source also uses the same interpolation type in all dimensions, if I'm correct? $\endgroup$ – jochim Feb 10 at 9:29
  • $\begingroup$ There is a bunch of different methods which are partly listed in the linked page. Have also a look at docs.scipy.org/doc/scipy/reference/interpolate.html This is a huge domain. $\endgroup$ – Claude Leibovici Feb 10 at 9:50
  • $\begingroup$ I'm familiar with multivariate interpolation in Matlab or using Scipy. Unfortunately, the interpolation method cannot be set to be different for each dimension for this available code. $\endgroup$ – jochim Feb 10 at 10:01

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