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GeDS  

Geometrically Designed Spline Regression
View on CRAN: Click here


Download and install GeDS package within the R console
Install from CRAN:
install.packages("GeDS")

Install from Github:
library("remotes")
install_github("cran/GeDS")

Install by package version:
library("remotes")
install_version("GeDS", "0.2.4")



Attach the package and use:
library("GeDS")
Maintained by
Emilio S. Guillen
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-11-08
Latest Update: 2017-12-19
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 modeling complex relationships. A description of the method can be found in Kaishev et al. (2016) and Dimitrova et al. (2023) . 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. (2024).
How to cite:
Emilio S. Guillen (2017). GeDS: Geometrically Designed Spline Regression. R package version 0.2.4, https://cran.r-project.org/web/packages/GeDS. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.1.2 (2017-11-08 20:24), 0.1.3 (2017-12-19 12:12), 0.1.4 (2023-12-06 11:00), 0.2.0 (2024-03-24 16:50), 0.2.1 (2024-04-12 00:00), 0.2.2 (2024-04-24 19:20), 0.2.3 (2024-07-19 16:30)
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