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Geometrically Designed Spline Regression

0packages depend
7.4Kdownloads / year
54.1%test coverage
13/13flavors OK

Overview

About

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).

Install

Health

CRAN checks
13OK
Slowest check: 12.3 min · r-oldrel-macos-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-07-18
  • NOTE12 OK, 2 NOTE2026-04-22
  • ERROR11 OK, 2 NOTE, 1 ERROR2026-04-18
Show 1 earlier changeHide 1 earlier change
  • NOTE12 OK, 2 NOTE2026-03-10
Advisories

none known

Documentation

In release 0.3.5
READMEYes · 106 wordsVignettesYes · 4 · dynamicNEWSNoCitation fileYes · computed when R runs itWebsitenot declared in DESCRIPTION
Help pages
41includes a package overview page
Examples that run
91%20 run in a plain check (1 of them under a condition) · 2 never run
Exported functions with examples
69%
Documented parameters
97%
Return-value docs
81%
Help pages citing references
37%

Downloads

7.4K
CRAN downloads in the past year
Rank #5,784 · ~20/day · ~618/mo
Daily download trend is not available in this view yet.
54630 days
1.4K90 days
7.4K1 year
Compare downloads with other packages →
Also on444 r2u1 autocran

Repository

2Stars
0Forks
1Open issues
0Open PRs
0Releases
78Commits
2Commit identities
78 commits · Last activity 2026-09-27 · Default branch at 0.3.6, ahead of CRAN 0.3.5 (checked 2026-10-22)
Responsiveness
not measured

Stars over time

2025-05-13 · 22026-07-07 · 2
PracticesBeta

3 development-tooling and community-health practices detected across 3 families in the upstream repository

Checks run against github.com/emilioluissaenzguillen/geds on 2026-10-22.

Continuous integration (1)
GitHub Actions
Lint, format, editor (1)
RStudio project
Git structural (1)
.gitattributes
How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies
16 external dependencies (excludes base and recommended)

Installing GeDS adds 25 packages (11 with compiled code, 13 MB of source tarballs). Heaviest: partykit 2.1 MB, mboost 2.0 MB, Rcpp 1.8 MB.

Depends (1)
R >= 4.4.0
Imports (15)
doFuturedoParalleldoRNGforeachfuturegraphicsgrDevicesMASSMatrixmboostparallelRcppsplinesstatsutils
LinkingTo (1)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (5)
Author, Maintainer since 0.1.4 (2023)

Previously maintained by Andrea Lattuada (0.1.2 to 0.1.3).

Listed in earlier versions (10)
Show 8 of 10 peopleHide 8 people
Emilio S. Guillen
no longer listed · 0.1.4 to 0.2.3
Dimitrova
no longer listed · 0.2.4 to 0.3.2
Guillen
no longer listed · 0.2.4
Kaishev
no longer listed · 0.2.4 to 0.3.2
Verrall
no longer listed · 0.2.4 to 0.3.2
Sáenz Guillén
no longer listed · 0.2.5 to 0.3.2
Richard J.
no longer listed · 0.3.3 to 0.3.5
Vladimir K.
no longer listed · 0.3.3 to 0.3.5
Releases (19)

Pick two releases to compare their code metrics.

Show 13 earlier eventsHide 13 earlier events
  • R
    R 4.4.0 released · 2024-04-24
  • 0.2.1
    record
    2024-04-12 · diff ↗
  • 0.2.0
    record
    2024-03-24 · diff ↗ ·
    added 6 exports
    BivariateFitter, GenBivariateFitter, NGeDSboost, NGeDSgam, bl_imp, visualize_boosting
  • 0.1.4
    record
    2023-12-06 · diff ↗
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • R
    R 4.0.0 released · 2020-04-24
  • R
    R 3.6.0 released · 2019-04-26
  • R
    R 3.5.0 released · 2018-04-23
  • 0.1.3
    record
    2017-12-19 · diff ↗
  • 0.1.2
    record
    2017-11-08
  • R
    R 3.4.0 released · 2017-04-21

Package metadata

First published
2017-11-08
Total releases
19 / 9 yrs
License
GPL-3 OSI
Minimum R
≥ 4.4.0
Bundled data
43 KB / 5 files
Download size
3.9 MB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("GeDS")

The package provides a citation file that builds its entry when R runs it. Run citation() to see it.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for GeDS version 0.3.5 [Data set]. HJJB, LLC. Data release v2026-10-23. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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