mgss: A Matrix-Free Multigrid Preconditioner for Spline Smoothing

Data smoothing with penalized splines is a popular method and is well established for one- or two-dimensional covariates. The extension to multiple covariates is straightforward but suffers from exponentially increasing memory requirements and computational complexity. This toolbox provides a matrix-free implementation of a conjugate gradient (CG) method for the regularized least squares problem resulting from tensor product B-spline smoothing with multivariate and scattered data. It further provides matrix-free preconditioned versions of the CG-algorithm where the user can choose between a simpler diagonal preconditioner and an advanced geometric multigrid preconditioner. The main advantage is that all algorithms are performed matrix-free and therefore require only a small amount of memory. For further detail see Siebenborn & Wagner (2021).

Version:	1.2
Depends:	R (≥ 3.5.0)
Imports:	Rcpp (≥ 1.0.5), combinat (≥ 0.0-8), statmod (≥ 1.1), Matrix (≥ 1.2)
LinkingTo:	Rcpp
Suggests:	testthat
Published:	2021-05-10
DOI:	10.32614/CRAN.package.mgss
Author:	Martin Siebenborn [aut, cre, cph], Julian Wagner [aut, cph]
Maintainer:	Martin Siebenborn <martin.siebenborn at uni-hamburg.de>
BugReports:	https://github.com/SplineSmoothing/MGSS
License:	MIT + file LICENSE
NeedsCompilation:	yes
CRAN checks:	mgss results

Documentation:

Reference manual:

mgss.pdf

Downloads:

Package source:	mgss_1.2.tar.gz
Windows binaries:	r-devel: mgss_1.2.zip, r-release: mgss_1.2.zip, r-oldrel: mgss_1.2.zip
macOS binaries:	r-release (arm64): mgss_1.2.tgz, r-oldrel (arm64): mgss_1.2.tgz, r-release (x86_64): mgss_1.2.tgz, r-oldrel (x86_64): mgss_1.2.tgz
Old sources:	mgss archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=mgss to link to this page.