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: 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 21 Apr. 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
Downloads during the last 30 days
03/2403/2703/2803/2903/3104/0104/0304/0404/0504/0604/0704/0804/1204/1304/1404/1604/1704/19Downloads for sglOptim05101520253035TrendBars

Today's Hot Picks in Authors and Packages

bssn  
Birnbaum-Saunders Model
It provides the density, distribution function, quantile function, random number generator, reliabil ...
Download / Learn more Package Citations See dependency  
r2resize  
In-Text Resize for Images, Tables and Fancy Resize Containers in 'shiny', 'rmarkdown' and 'quarto' Documents
Automatic resizing toolbar for containers, images and tables. Various resizable or expandable contai ...
Download / Learn more Package Citations See dependency  
discretecdAlgorithm  
Coordinate-Descent Algorithm for Learning Sparse Discrete Bayesian Networks
Structure learning of Bayesian network using coordinate-descent algorithm. This algorithm is design ...
Download / Learn more Package Citations See dependency  
HellCor  
The Hellinger Correlation
Empirical value of the Hellinger correlation, a measure of dependence between two continuous random ...
Download / Learn more Package Citations See dependency  
bigsparser  
Sparse Matrix Format with Data on Disk
Provide a sparse matrix format with data stored on disk, to be used in both R and C++. This is inte ...
Download / Learn more Package Citations See dependency  

24,098

R Packages

207,311

Dependencies

65,069

Author Associations

24,099

Publication Badges

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