Other packages > Find by keyword >

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:
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 07 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:03), 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
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

ggTimeSeries  
Time Series Visualisations Using the Grammar of Graphics
Provides additional display mediums for time series visualisations. ...
Download / Learn more Package Citations See dependency  
PairedData  
Paired Data Analysis
Many datasets and a set of graphics (based on ggplot2), statistics, effect sizes and hypothesis test ...
Download / Learn more Package Citations See dependency  
splm  
Econometric Models for Spatial Panel Data
ML and GM estimation and diagnostic testing of econometric models for spatial panel data. ...
Download / Learn more Package Citations See dependency  
skewlmm  
Scale Mixture of Skew-Normal Linear Mixed Models
It fits scale mixture of skew-normal linear mixed models using an expectation–maximization (EM) ty ...
Download / Learn more Package Citations See dependency  
blandr  
Bland-Altman Method Comparison
Carries out Bland Altman analyses (also known as a Tukey mean-difference plot) as described by JM B ...
Download / Learn more Package Citations See dependency  
nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  

28,905

R Packages

247,686

Dependencies

76,495

Author Associations

28,906

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA