The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

mixedLSR: Mixed, Low-Rank, and Sparse Multivariate Regression on High-Dimensional Data

Mixed, low-rank, and sparse multivariate regression ('mixedLSR') provides tools for performing mixture regression when the coefficient matrix is low-rank and sparse. 'mixedLSR' allows subgroup identification by alternating optimization with simulated annealing to encourage global optimum convergence. This method is data-adaptive, automatically performing parameter selection to identify low-rank substructures in the coefficient matrix.

Version: 0.1.0
Depends: R (≥ 4.1.0)
Imports: grpreg, purrr, MASS, stats, ggplot2
Suggests: knitr, rmarkdown, mclust
Published: 2022-11-04
DOI: 10.32614/CRAN.package.mixedLSR
Author: Alexander White ORCID iD [aut, cre], Sha Cao ORCID iD [aut], Yi Zhao ORCID iD [ctb], Chi Zhang ORCID iD [ctb]
Maintainer: Alexander White <whitealj at iu.edu>
BugReports: https://github.com/alexanderjwhite/mixedLSR
License: MIT + file LICENSE
URL: https://alexanderjwhite.github.io/mixedLSR/
NeedsCompilation: no
Materials: README NEWS
CRAN checks: mixedLSR results

Documentation:

Reference manual: mixedLSR.pdf
Vignettes: Introduction to mixedLSR

Downloads:

Package source: mixedLSR_0.1.0.tar.gz
Windows binaries: r-devel: mixedLSR_0.1.0.zip, r-release: mixedLSR_0.1.0.zip, r-oldrel: mixedLSR_0.1.0.zip
macOS binaries: r-release (arm64): mixedLSR_0.1.0.tgz, r-oldrel (arm64): mixedLSR_0.1.0.tgz, r-release (x86_64): mixedLSR_0.1.0.tgz, r-oldrel (x86_64): mixedLSR_0.1.0.tgz

Linking:

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

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.