Package: drrglm 0.4.0

Zengchao Xu

drrglm: Doubly Regularized Matrix-Variate Regression

The doubly regularized matrix-variate regression solves a low-rank-plus-sparse structure for matrix-variate generalized linear models through a weighted combination of nuclear-norm and L1-norm. The methodology implemented by this package is described in the paper "Doubly Regularized Matrix-Variate Regression". See Xu, Luo and Jiang <doi:10.1080/10618600.2026.2702534>.

Authors:Zengchao Xu [aut, cre, cph], Shan Luo [aut], Binyan Jiang [aut]

drrglm_0.4.0.tar.gz
drrglm_0.4.0.zip(r-4.7-x86_64)drrglm_0.4.0.zip(r-4.7-arm64)drrglm_0.4.0.zip(r-4.6-x86_64)drrglm_0.4.0.zip(r-4.6-arm64)drrglm_0.4.0.zip(r-4.5-x86_64)
drrglm_0.4.0.tgz(r-4.6-x86_64)drrglm_0.4.0.tgz(r-4.6-arm64)drrglm_0.4.0.tgz(r-4.5-x86_64)drrglm_0.4.0.tgz(r-4.5-arm64)
drrglm_0.4.0.tar.gz(r-4.7-arm64)drrglm_0.4.0.tar.gz(r-4.7-x86_64)drrglm_0.4.0.tar.gz(r-4.6-arm64)drrglm_0.4.0.tar.gz(r-4.6-x86_64)
drrglm_0.4.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
drrglm/json (API)

# Install 'drrglm' in R:
install.packages('drrglm', repos = c('https://paradoxical-rhapsody.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/paradoxical-rhapsody/drrglm/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • EEG - ElectroEncephaloGraphy Data

On CRAN:

Conda:

openblascpp

3.48 score 346 downloads 9 exports 12 dependencies

Last updated from:f81c67be90. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK155
linux-devel-x86_64OK156
source / vignettesOK189
linux-release-arm64OK140
linux-release-x86_64OK129
macos-release-arm64OK134
macos-release-x86_64OK394
macos-oldrel-arm64OK122
macos-oldrel-x86_64OK284
windows-devel-arm64OK219
windows-devel-x86_64OK159
windows-release-arm64OK221
windows-release-x86_64OK120
windows-oldrel-x86_64OK147
wasm-releaseOK123

Exports:drrglmini_parassimu_factor_model_datasimu_factor_model_parassimu_reg_coefssimu_reg_datasimu_zhouandli2014tune_drr_factor_modeltune_drrglm

Dependencies:codetoolsdata.tableforeachglmnetiteratorslatticeMatrixRcppRcppArmadilloRcppEigenshapesurvival