Package: mgss
Type: Package
Title: A Matrix-Free Multigrid Preconditioner for Spline Smoothing
Version: 1.2
Authors@R: c(
                person("Martin", "Siebenborn", role = c("aut", "cre", "cph"),
                        email = "martin.siebenborn@uni-hamburg.de"),
                person("Julian", "Wagner", role = c("aut", "cph"),
                        email = "juwagn89@gmail.com")
            )
Description: 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).
License: MIT + file LICENSE
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.5), combinat (>= 0.0-8), statmod (>= 1.1), Matrix
        (>= 1.2)
LinkingTo: Rcpp
RoxygenNote: 7.1.1
Encoding: UTF-8
Repository: CRAN
Suggests: testthat
BugReports: https://github.com/SplineSmoothing/MGSS
NeedsCompilation: yes
Packaged: 2021-05-07 13:43:38 UTC; martin
Author: Martin Siebenborn [aut, cre, cph],
  Julian Wagner [aut, cph]
Maintainer: Martin Siebenborn <martin.siebenborn@uni-hamburg.de>
Date/Publication: 2021-05-10 07:50:06 UTC
Built: R 4.3.0; x86_64-apple-darwin20; 2023-07-11 22:36:46 UTC; unix
Archs: mgss.so.dSYM
