Type: Package
Package: GeDS
Title: Geometrically Designed Spline Regression
Version: 0.3.4
Date: 2026-07-14
Authors@R: c(
    person(c("Dimitrina", "S."), "Dimitrova", , "D.Dimitrova@citystgeorges.ac.uk", role = "aut"),
    person(c("Vladimir", "K."), "Kaishev", , "Vladimir.Kaishev.1@citystgeorges.ac.uk", role = "aut"),
    person("Andrea", "Lattuada", , "Andrea.Lattuada@hotmail.com", role = "aut"),
    person(c("Emilio", "L."), "Sáenz Guillén", , "emilioluissaenzguillen@gmail.com", role = c("aut", "cre")),
    person(c("Richard", "J."), "Verrall", , "R.J.Verrall@citystgeorges.ac.uk", role = "aut")
  )
Maintainer: Emilio L. Sáenz Guillén <emilioluissaenzguillen@gmail.com>
Description: Spline regression, generalized additive models and
        component-wise gradient boosting utilizing geometrically
        designed (GeD) splines. GeDS regression is a non-parametric
        method inspired by geometric principles, for fitting spline
        regression models with variable knots in one or two independent
        variables. It efficiently estimates the number of knots and
        their positions, as well as the spline order, assuming the
        response variable follows a distribution from the exponential
        family. GeDS models integrate the broader category of
        generalized (non-)linear models, offering a flexible approach
        to model complex relationships. A description of the method can
        be found in Kaishev et al. (2016)
        <doi:10.1007/s00180-015-0621-7> and Dimitrova et al. (2023)
        <doi:10.1016/j.amc.2022.127493>. Further extending its
        capabilities, GeDS's implementation includes generalized
        additive models (GAM) and functional gradient boosting (FGB),
        enabling versatile multivariate predictor modeling, as
        discussed in the forthcoming work of Dimitrova et al. (2026).
License: GPL-3
URL: https://github.com/emilioluissaenzguillen/GeDS
BugReports: https://github.com/emilioluissaenzguillen/GeDS/issues
Depends: R (>= 4.4.0)
Imports: doFuture, doParallel, doRNG, foreach, future, graphics,
        grDevices, MASS, Matrix, mboost, parallel, Rcpp, splines,
        stats, utils
Suggests: AmesHousing, knitr, plot3D, quadprog, R.rsp, rmarkdown,
        rpart, testthat (>= 3.0.0), TH.data
LinkingTo: Rcpp
VignetteBuilder: knitr, R.rsp
Config/testthat/edition: 3
Encoding: UTF-8
LazyData: TRUE
Config/roxygen2/version: 8.0.0
Repository: https://emilioluissaenzguillen.r-universe.dev
Date/Publication: 2026-07-14 18:32:04 UTC
RemoteUrl: https://github.com/emilioluissaenzguillen/geds
RemoteRef: HEAD
RemoteSha: dbed4549a65002d6c2cdd5df8b2bc9c058a59b2e
NeedsCompilation: yes
Packaged: 2026-07-14 19:18:13 UTC; root
Author: Dimitrina S. Dimitrova [aut],
  Vladimir K. Kaishev [aut],
  Andrea Lattuada [aut],
  Emilio L. Sáenz Guillén [aut, cre],
  Richard J. Verrall [aut]