Generic Sparse Group Lasso Solver

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Documentation for package ‘sglOptim’ version 1.3.8

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

sglOptim-package	sglOptim: Generic Sparse Group Lasso Solver
add_data	Add data to a sgldata data object
add_data.sgldata	Add data to a sgldata data object
best_model	Index of best model
best_model.sgl	Index of best model
coef.sgl	Extracting the nonzero coefficients
compute_error	Helper function for computing error rates
create.sgldata	Create a sgldata object
element_class	Retur the element class of an object.
Err	Generic function for computing error rates
Err.sgl	Error Rates
features	Extracts nonzero features
features.sgl	Extracting nonzero features
features_stat	Extract feature statistics
features_stat.sgl	Extract feature statistics
get_coef	Get the nonzero coefficients
models	Extract fitted models
models.sgl	Extract the estimated models
nmod	Number of models used for fitting
nmod.sgl	Returns the number of models in a sgl object
parameters	Extracts nonzero parameters
parameters.sgl	Extracting nonzero parameters
parameters_stat	Extract parameter statistics
parameters_stat.sgl	Extracting parameter statistics
prepare.args	Generic function for preparing the sgl call arguments
prepare.args.sgldata	Prepare sgl function arguments
prepare_data	Prepare a sgldata data object
print_with_metric_prefix	Print a numeric with metric prefix
rearrange	Generic rearrange function
rearrange.sgldata	Rearrange sgldata
sgl.algorithm.config	Create a new algorithm configuration
sgl.c.config	Featch information about the C side configuration of the package
sgl.standard.config	Standard algorithm configuration
sglOptim	sglOptim: Generic Sparse Group Lasso Solver
sgl_cv	Generic sparse group lasso cross validation using multiple possessors
sgl_fit	Fit a Sparse Group Lasso Regularization Path.
sgl_lambda_sequence	Computing a Lambda Sequence
sgl_predict	Predict
sgl_print	Print information about sgl object
sgl_subsampling	Generic sparse group lasso subsampling procedure
sgl_test	Test a sgl-Objective
sparseMatrix_from_C_format	Convert to sparse matrix
sparseMatrix_to_C_format	Prepare sparse matrix for .Call
subsample	Subsample
subsample.sgldata	Subsample sgldata
test.data	Simulated data set
test_rtools	Test internal rtools
transpose_response_elements	Transpose response elements