Package: sparsegl 1.1.0

Daniel J. McDonald

sparsegl:Sparse Group Lasso

Efficient implementation of sparse group lasso with optional bound constraints on the coefficients. It supports the use of a sparse design matrix as well as returning coefficient estimates in a sparse matrix. Furthermore, it correctly calculates the degrees of freedom to allow for information criteria rather than cross-validation with very large data. Finally, the interface to compiled code avoids unnecessary copies and allows for the use of long integers.

Authors:Daniel J. McDonald [aut, cre], Xiaoxuan Liang [aut], Anibal Solón Heinsfeld [aut], Aaron Cohen [aut], Yi Yang [ctb], Hui Zou [ctb], Jerome Friedman [ctb], Trevor Hastie [ctb], Rob Tibshirani [ctb], Balasubramanian Narasimhan [ctb], Kenneth Tay [ctb], Noah Simon [ctb], Junyang Qian [ctb], James Yang [ctb]

sparsegl_1.1.0.tar.gz
sparsegl_1.1.0.tar.gz(r-4.5-noble)sparsegl_1.1.0.tar.gz(r-4.4-noble)
sparsegl_1.1.0.tgz(r-4.4-emscripten)sparsegl_1.1.0.tgz(r-4.3-emscripten)
sparsegl.pdf |sparsegl.html
sparsegl/json (API)
NEWS

# Installsparsegl in R:
install.packages('sparsegl',repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/dajmcdon/sparsegl/issues

Uses libs:
  • fortran– Runtime library for GNU Fortran applications
Datasets:
  • trust_experts - Trust in scientific experts during the Covid-19 pandemic

15 exports 0.61 score 40 dependencies 1 dependents 329 downloads

Last updated 9 days agofrom:f8704ee5f4

Exports:%>%cv.sparseglestimate_riskgr_one_normgr_two_normgrouped_one_normgrouped_sp_normgrouped_two_normgrouped_zero_normmake_irls_warmupone_normsp_group_normsparsegltwo_normzero_norm

Dependencies:clicolorspacecpp11dotCall64dplyrfansifarvergenericsggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigpurrrR6RColorBrewerRcppRcppEigenrlangRSpectrascalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr

Getting started with sparsegl

Rendered fromsparsegl.Rmdusingknitr::rmarkdownon Jun 27 2024.

Last update: 2024-06-27
Started: 2022-03-07