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mixedLSR  

Mixed, Low-Rank, and Sparse Multivariate Regression on High-Dimensional Data
View on CRAN: Click here


Download and install mixedLSR package within the R console
Install from CRAN:
install.packages("mixedLSR")

Install from Github:
library("remotes")
install_github("cran/mixedLSR")

Install by package version:
library("remotes")
install_version("mixedLSR", "0.1.0")



Attach the package and use:
library("mixedLSR")
Maintained by
Alexander White
[Scholar Profile | Author Map]
First Published: 2022-11-04
Latest Update: 2022-11-04
Description:
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.
How to cite:
Alexander White (2022). mixedLSR: Mixed, Low-Rank, and Sparse Multivariate Regression on High-Dimensional Data. R package version 0.1.0, https://cran.r-project.org/web/packages/mixedLSR. Accessed 01 May. 2025.
Previous versions and publish date:
No previous versions
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Complete documentation for mixedLSR
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