Package: mgss 1.2

Martin Siebenborn

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).

Authors:Martin Siebenborn [aut, cre, cph], Julian Wagner [aut, cph]

mgss_1.2.tar.gz
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mgss_1.2.tar.gz(r-4.5-noble)mgss_1.2.tar.gz(r-4.4-noble)
mgss_1.2.tgz(r-4.4-emscripten)mgss_1.2.tgz(r-4.3-emscripten)
mgss.pdf |mgss.html
mgss/json (API)

# Install 'mgss' in R:
install.packages('mgss', repos = c('https://splinesmoothing.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/splinesmoothing/mgss/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

6 exports 0.73 score 5 dependencies 3 scripts 156 downloads

Last updated 3 years agofrom:3b7dd9e847. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 10 2024
R-4.5-win-x86_64NOTESep 10 2024
R-4.5-linux-x86_64NOTESep 10 2024
R-4.4-win-x86_64NOTESep 10 2024
R-4.4-mac-x86_64NOTESep 10 2024
R-4.4-mac-aarch64NOTESep 10 2024
R-4.3-win-x86_64NOTESep 10 2024
R-4.3-mac-x86_64NOTESep 10 2024
R-4.3-mac-aarch64NOTESep 10 2024

Exports:CG_smoothestimate_tracegenerate_test_dataMGCG_smoothPCG_smoothpredict_smooth

Dependencies:combinatlatticeMatrixRcppstatmod