Package: gofar 0.1

Aditya Mishra

gofar: Generalized Co-Sparse Factor Regression

Divide and conquer approach for estimating low-rank and sparse coefficient matrix in the generalized co-sparse factor regression. Please refer the manuscript 'Mishra, Aditya, Dipak K. Dey, Yong Chen, and Kun Chen. Generalized co-sparse factor regression. Computational Statistics & Data Analysis 157 (2021): 107127' for more details.

Authors:Aditya Mishra [aut, cre], Kun Chen [aut]

gofar_0.1.tar.gz
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gofar.pdf |gofar.html✨
gofar/json (API)

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

Peer review:

Bug tracker:https://github.com/amishra-stats/gofar/issues

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

On CRAN:

3.00 score 2 stars 1 scripts 143 downloads 4 exports 38 dependencies

Last updated 3 years agofrom:429e113be9. Checks:OK: 1 WARNING: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 07 2024
R-4.5-win-x86_64WARNINGNov 07 2024
R-4.5-linux-x86_64WARNINGNov 07 2024
R-4.4-win-x86_64WARNINGNov 07 2024
R-4.4-mac-x86_64WARNINGNov 07 2024
R-4.4-mac-aarch64WARNINGNov 07 2024
R-4.3-win-x86_64WARNINGNov 07 2024
R-4.3-mac-x86_64WARNINGNov 07 2024
R-4.3-mac-aarch64WARNINGNov 07 2024

Exports:gofar_controlgofar_pgofar_sgofar_sim

Dependencies:clicodetoolscolorspacefansifarverforeachggplot2glmnetgluegtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppArmadilloRcppEigenrlangrrpackscalesshapesurvivaltibbleutf8vctrsviridisLitewithr