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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) and Dimitrova et al. (2023).
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This package is free and open source software, licensed under GPL-3
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They may not be fully stable and should be used with caution. We make no claims about them.
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