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:	0.1.3
Depends:	R (≥ 3.0.1), Rcpp (≥ 0.12.1), splines, stats, utils, Matrix, methods, Rmpfr
LinkingTo:	Rcpp
Published:	2017-12-19
Author:	Dimitrina S. Dimitrova, Vladimir K. Kaishev, Andrea Lattuada and Richard J. Verrall
Maintainer:	Andrea Lattuada <Andrea.Lattuada at unicatt.it>
BugReports:	http://github.com/alattuada/GeDS/issues
License:	GPL-3
URL:	http://github.com/alattuada/GeDS
NeedsCompilation:	yes
Citation:	GeDS citation info
CRAN checks:	GeDS results

Documentation:

Reference manual:

GeDS.pdf

Downloads:

Package source:	GeDS_0.1.3.tar.gz
Windows binaries:	r-devel: GeDS_0.1.3.zip, r-release: GeDS_0.1.3.zip, r-oldrel: GeDS_0.1.3.zip
macOS binaries:	r-release (arm64): GeDS_0.1.3.tgz, r-release (x86_64): GeDS_0.1.3.tgz, r-oldrel: GeDS_0.1.3.tgz
Old sources:	GeDS archive

Linking:

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