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) <https://openaccess.city.ac.uk/18460>.

Version: 0.1.2
Depends: R (≥ 3.0.1), Rcpp (≥ 0.12.1), splines, stats, utils, Matrix, methods, Rmpfr
LinkingTo: Rcpp
Published: 2017-11-08
Author: Dimitrina S. Dimitrova, Vladimir K. Kaishev, Andrea Lattuada and Richard J. Verrall
Maintainer: Andrea Lattuada <Andrea.Lattuada at unicatt.it>
License: GPL-3
NeedsCompilation: yes
Citation: GeDS citation info
CRAN checks: GeDS results

Downloads:

Reference manual: GeDS.pdf
Package source: GeDS_0.1.2.tar.gz
Windows binaries: r-devel: GeDS_0.1.2.zip, r-release: GeDS_0.1.2.zip, r-oldrel: GeDS_0.1.2.zip
OS X El Capitan binaries: r-release: GeDS_0.1.2.tgz
OS X Mavericks binaries: r-oldrel: GeDS_0.1.2.tgz

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