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mixedLSR
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]
[Scholar Profile | Author Map]
All associated links for this package
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 26 Jun. 2026.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for mixedLSR
Functions, R codes and Examples using
the mixedLSR R package
Some associated functions: bic_lsr . fct_alt_optimize . fct_dpp . fct_em . fct_gamma . fct_initialize . fct_j_lik . fct_log_lik . fct_new_assign . fct_pi_vec . fct_rank . fct_select_lambda . fct_sigma . fct_sim_anneal . fct_weighted_ll . mixed_lsr . plot_lsr . simulate_lsr .
Some associated R codes: bic_lsr.R . fct_alt_optimize.R . fct_dpp.R . fct_em.R . fct_gamma.R . fct_initialize.R . fct_j_lik.R . fct_log_lik.R . fct_new_assign.R . fct_pi_vec.R . fct_rank.R . fct_select_lambda.R . fct_sigma.R . fct_sim_anneal.R . fct_weighted_ll.R . mixed_lsr.R . plot_lsr.R . simulate_lsr.R . Full mixedLSR package functions and examples
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