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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.

Versions across snapshots

VersionRepositoryFileSize
0.1.0 rolling linux/jammy R-4.5 mixedLSR_0.1.0.tar.gz 186.0 KiB
0.1.0 rolling linux/noble R-4.5 mixedLSR_0.1.0.tar.gz 186.0 KiB
0.1.0 rolling source/ R- mixedLSR_0.1.0.tar.gz 127.1 KiB
0.1.0 latest linux/jammy R-4.5 mixedLSR_0.1.0.tar.gz 186.0 KiB
0.1.0 latest linux/noble R-4.5 mixedLSR_0.1.0.tar.gz 186.0 KiB
0.1.0 latest source/ R- mixedLSR_0.1.0.tar.gz 127.1 KiB
0.1.0 2026-04-26 source/ R- mixedLSR_0.1.0.tar.gz 127.1 KiB
0.1.0 2026-04-23 source/ R- mixedLSR_0.1.0.tar.gz 127.1 KiB
0.1.0 2026-04-09 windows/windows R-4.5 mixedLSR_0.1.0.zip 189.0 KiB
0.1.0 2025-04-20 source/ R- mixedLSR_0.1.0.tar.gz 127.1 KiB

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