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Description

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.

mixedLSR

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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.

Installation

You can install the development version of mixedLSR from GitHub with:

# install.packages("devtools")
devtools::install_github("alexanderjwhite/mixedLSR")
Metadata

Version

0.1.0

License

Unknown

Platforms (75)

    Darwin
    FreeBSD
    Genode
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    MMIXware
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