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MatrixModels: Modelling with Sparse and Dense Matrices

Modelling with sparse and dense 'Matrix' matrices, using modular prediction and response module classes.

Version: 0.5-3
Depends: R (≥ 3.6.0)
Imports: stats, methods, Matrix (≥ 1.6-0)
Published: 2023-11-06
DOI: 10.32614/CRAN.package.MatrixModels
Author: Douglas Bates and Martin Maechler
Maintainer: Martin Maechler <mmaechler+Matrix at gmail.com>
Contact: Matrix-authors@R-project.org
BugReports: https://R-forge.R-project.org/tracker/?func=add&atid=294&group_id=61
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://Matrix.R-forge.R-project.org/, https://r-forge.r-project.org/R/?group_id=61
NeedsCompilation: no
Materials: ChangeLog
CRAN checks: MatrixModels results

Documentation:

Reference manual: MatrixModels.pdf

Downloads:

Package source: MatrixModels_0.5-3.tar.gz
Windows binaries: r-devel: MatrixModels_0.5-3.zip, r-release: MatrixModels_0.5-3.zip, r-oldrel: MatrixModels_0.5-3.zip
macOS binaries: r-release (arm64): MatrixModels_0.5-3.tgz, r-oldrel (arm64): MatrixModels_0.5-3.tgz, r-release (x86_64): MatrixModels_0.5-3.tgz, r-oldrel (x86_64): MatrixModels_0.5-3.tgz
Old sources: MatrixModels archive

Reverse dependencies:

Reverse depends: RGE
Reverse imports: BayesESS, BayesFactor, diagL1, inlabru, pre, projectR, QTOCen, quantreg, twang, twangRDC
Reverse suggests: abn, BayesfMRI, car, ClassifyR

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.