GeDS (0.1.3)

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Geometrically Designed Spline Regression.

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. (2017) .

Maintainer: Andrea Lattuada
Author(s): Dimitrina S. Dimitrova <>, Vladimir K. Kaishev <>, Andrea Lattuada <> and Richard J. Verrall <>

License: GPL-3

Uses: Matrix, Rcpp, Rmpfr

Released about 2 years ago.

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