Geometrically Designed Spline ('GeDS') Regression is a non-parametric geometrically
motivated method for fitting variable knots spline predictor models in one or two independent
variables, in the context of generalized (non-)linear models. 'GeDS' estimates the number and
position of the knots and the order of the spline, assuming the response variable has a
distribution from the exponential family. A description of the method can be found in
Kaishev et al. (2016)