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sglOptim  

Generic Sparse Group Lasso Solver
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("sglOptim", "1.3.8")



Attach the package and use:
library("sglOptim")
Maintained by
Niels Richard Hansen
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2013-12-08
Latest Update: 2024-01-12
Description:
Fast generic solver for sparse group lasso optimization problems. The loss (objective) function must be defined in a C++ module. The optimization problem is solved using a coordinate gradient descent algorithm. Convergence of the algorithm is established (see reference) and the algorithm is applicable to a broad class of loss functions. Use of parallel computing for cross validation and subsampling is supported through the 'foreach' and 'doParallel' packages. Development version is on GitHub, please report package issues on GitHub.
How to cite:
Niels Richard Hansen (2013). sglOptim: Generic Sparse Group Lasso Solver. R package version 1.3.8, https://cran.r-project.org/web/packages/sglOptim. Accessed 28 Mar. 2025.
Previous versions and publish date:
0.0.80 (2013-12-08 20:33), 0.0.81 (2014-01-24 12:30), 0.0.82 (2014-02-19 13:44), 0.0.90 (2014-02-22 15:00), 0.0.91 (2014-02-23 22:05), 0.0.100 (2014-03-05 21:16), 0.0.105 (2014-03-10 22:20), 1.0.122.0 (2014-03-24 06:44), 1.0.122.1 (2014-11-04 20:11), 1.2.0 (2015-09-19 22:46), 1.2.2 (2016-09-10 19:17), 1.3.0 (2016-09-28 17:10), 1.3.5 (2016-12-29 01:09), 1.3.6 (2017-04-02 19:41), 1.3.7 (2018-10-21 09:30), 1.3.8 (2019-05-08 00:11)
Other packages that cited sglOptim R package
View sglOptim citation profile
Other R packages that sglOptim depends, imports, suggests or enhances
Functions, R codes and Examples using the sglOptim R package
Some associated functions: Err . Err.sgl . add_data . add_data.sgldata . best_model . best_model.sgl . coef.sgl . compute_error . create.sgldata . element_class . features . features.sgl . features_stat . features_stat.sgl . get_coef . linear_test_block_diagonal_sgl_fit_R . linear_test_block_diagonal_sgl_lambda_R . linear_test_block_diagonal_sgl_predict_R . linear_test_block_diagonal_sgl_subsampling_R . linear_test_block_diagonal_sgl_test_R . linear_test_block_diagonal_spx_sgl_fit_R . linear_test_block_diagonal_spx_sgl_lambda_R . linear_test_block_diagonal_spx_sgl_predict_R . linear_test_block_diagonal_spx_sgl_subsampling_R . linear_test_block_diagonal_spx_sgl_test_R . linear_test_block_diagonal_spx_spy_sgl_fit_R . linear_test_block_diagonal_spx_spy_sgl_lambda_R . linear_test_block_diagonal_spx_spy_sgl_predict_R . linear_test_block_diagonal_spx_spy_sgl_subsampling_R . linear_test_block_diagonal_spx_spy_sgl_test_R . linear_test_block_diagonal_spy_sgl_fit_R . linear_test_block_diagonal_spy_sgl_lambda_R . linear_test_block_diagonal_spy_sgl_predict_R . linear_test_block_diagonal_spy_sgl_subsampling_R . linear_test_block_diagonal_spy_sgl_test_R . linear_test_diagonal_error_w_sgl_fit_R . linear_test_diagonal_error_w_sgl_lambda_R . linear_test_diagonal_error_w_sgl_test_R . linear_test_diagonal_w_sgl_fit_R . linear_test_diagonal_w_sgl_lambda_R . linear_test_diagonal_w_sgl_predict_R . linear_test_diagonal_w_sgl_subsampling_R . linear_test_diagonal_w_sgl_test_R . linear_test_diagonal_w_spx_sgl_fit_R . linear_test_diagonal_w_spx_sgl_lambda_R . linear_test_diagonal_w_spx_sgl_predict_R . linear_test_diagonal_w_spx_sgl_subsampling_R . linear_test_diagonal_w_spx_sgl_test_R . linear_test_diagonal_w_spx_spy_sgl_fit_R . linear_test_diagonal_w_spx_spy_sgl_lambda_R . linear_test_diagonal_w_spx_spy_sgl_predict_R . linear_test_diagonal_w_spx_spy_sgl_subsampling_R . linear_test_diagonal_w_spx_spy_sgl_test_R . linear_test_diagonal_w_spy_sgl_fit_R . linear_test_diagonal_w_spy_sgl_lambda_R . linear_test_diagonal_w_spy_sgl_predict_R . linear_test_diagonal_w_spy_sgl_subsampling_R . linear_test_diagonal_w_spy_sgl_test_R . linear_test_full_sgl_fit_R . linear_test_full_sgl_lambda_R . linear_test_full_sgl_predict_R . linear_test_full_sgl_subsampling_R . linear_test_full_sgl_test_R . linear_test_full_spx_sgl_fit_R . linear_test_full_spx_sgl_lambda_R . linear_test_full_spx_sgl_predict_R . linear_test_full_spx_sgl_subsampling_R . linear_test_full_spx_sgl_test_R . linear_test_full_spx_spy_sgl_fit_R . linear_test_full_spx_spy_sgl_lambda_R . linear_test_full_spx_spy_sgl_predict_R . linear_test_full_spx_spy_sgl_subsampling_R . linear_test_full_spx_spy_sgl_test_R . linear_test_full_spy_sgl_fit_R . linear_test_full_spy_sgl_lambda_R . linear_test_full_spy_sgl_predict_R . linear_test_full_spy_sgl_subsampling_R . linear_test_full_spy_sgl_test_R . linear_test_identity_sgl_fit_R . linear_test_identity_sgl_lambda_R . linear_test_identity_sgl_predict_R . linear_test_identity_sgl_subsampling_R . linear_test_identity_sgl_test_R . linear_test_identity_spx_sgl_fit_R . linear_test_identity_spx_sgl_lambda_R . linear_test_identity_spx_sgl_predict_R . linear_test_identity_spx_sgl_subsampling_R . linear_test_identity_spx_sgl_test_R . linear_test_identity_spx_spy_sgl_fit_R . linear_test_identity_spx_spy_sgl_lambda_R . linear_test_identity_spx_spy_sgl_predict_R . linear_test_identity_spx_spy_sgl_subsampling_R . linear_test_identity_spx_spy_sgl_test_R . linear_test_identity_spy_sgl_fit_R . linear_test_identity_spy_sgl_lambda_R . linear_test_identity_spy_sgl_predict_R . linear_test_identity_spy_sgl_subsampling_R . linear_test_identity_spy_sgl_test_R . models . models.sgl . nmod . nmod.sgl . parameters . parameters.sgl . parameters_stat . parameters_stat.sgl . prepare.args . prepare.args.sgldata . prepare_data . print_with_metric_prefix . rearrange . rearrange.sgldata . sgl.algorithm.config . sgl.c.config . sgl.standard.config . sglOptim . sgl_cv . sgl_fit . sgl_lambda_sequence . sgl_predict . sgl_print . sgl_subsampling . sgl_test . sparseMatrix_from_C_format . sparseMatrix_to_C_format . subsample . subsample.sgldata . test.data . test_rtools . transpose_response_elements . 
Some associated R codes: lambda_sequence.R . only_for_testing.R . prepare_args.R . response_formatter.R . rtools_test.R . sglOptim.R . sgl_config.R . sgl_cv.R . sgl_error.R . sgl_fit.R . sgl_navigate.R . sgl_predict.R . sgl_subsampling.R . sgl_test.R . startup.R .  Full sglOptim package functions and examples
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