GeDS: 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) <doi:10.1007/s00180-015-0621-7> and Dimitrova et al. (2017) <>.

Version: 0.1.4
Depends: R (≥ 3.0.1), Rcpp (≥ 0.12.1), splines, stats, utils, Matrix, methods, Rmpfr
LinkingTo: Rcpp
Published: 2023-12-06
Author: Dimitrina S. Dimitrova, Emilio S. Guillen, Vladimir K. Kaishev, Andrea Lattuada and Richard J. Verrall
Maintainer: Emilio S. Guillen <emilio.saenz-guillen at>
License: GPL-3
NeedsCompilation: yes
Citation: GeDS citation info
Materials: README
CRAN checks: GeDS results


Reference manual: GeDS.pdf


Package source: GeDS_0.1.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): GeDS_0.1.4.tgz, r-oldrel (arm64): GeDS_0.1.4.tgz, r-release (x86_64): GeDS_0.1.4.tgz
Old sources: GeDS archive


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