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Splinets  

Functional Data Analysis using Splines and Orthogonal Spline Bases
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("Splinets", "1.5.1")



Attach the package and use:
library("Splinets")
Maintained by
Krzysztof Podgorski
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-03-12
Latest Update: 2025-01-28
Description:
Splines are efficiently represented through their Taylor expansion at the knots. The representation accounts for the support sets and is thus suitable for sparse functional data. Two cases of boundary conditions are considered: zero-boundary or periodic-boundary for all derivatives except the last. The periodical splines are represented graphically using polar coordinates. The B-splines and orthogonal bases of splines that reside on small total support are implemented. The orthogonal bases are referred to as 'splinets' and are utilized for functional data analysis. Random spline generator is implemented as well asall fundamental algebraic and calculus operations on splines.The optimal, in the least square sense, functional fit by 'splinets' to data consisting of sampled values of functions as well as splines build over another set of knots is obtained and used for functional data analysis.<doi:10.48550/arXiv.2102.00733>, <doi:10.1016/j.cam.2022.114444>,<doi:10.48550/arXiv.2302.07552>.
How to cite:
Krzysztof Podgorski (2021). Splinets: Functional Data Analysis using Splines and Orthogonal Spline Bases. R package version 1.5.1, https://cran.r-project.org/web/packages/Splinets. Accessed 27 Oct. 2026.
Previous versions and publish date:
(2026-07-09 08:26), 1.0.0 (2021-03-12 10:20), 1.5.0 (2023-03-06 20:40)
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