Package: glmtlp 2.0.2

glmtlp: Generalized Linear Models with Truncated Lasso Penalty

Extremely efficient procedures for fitting regularization path with l0, l1, and truncated lasso penalty for linear regression and logistic regression models. This version is a completely new version compared with our previous version, which was mainly based on R. New core algorithms are developed and are now written in C++ and highly optimized.

Authors:Chunlin Li [aut, cph], Yu Yang [aut, cre, cph], Chong Wu [aut, cph], Xiaotong Shen [ths, cph], Wei Pan [ths, cph]

glmtlp_2.0.2.tar.gz
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glmtlp.pdf |glmtlp.html
glmtlp/json (API)
NEWS

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

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • bin_data - A simulated binomial data set.
  • gau_data - A simulated gaussian data set.

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.52 score 33 scripts 346 downloads 10 exports 32 dependencies

Last updated 2 months agofrom:0cc1c1e6bc. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 02 2024
R-4.5-win-x86_64OKNov 02 2024
R-4.5-linux-x86_64OKNov 02 2024
R-4.4-win-x86_64OKNov 02 2024
R-4.4-mac-x86_64OKNov 02 2024
R-4.4-mac-aarch64OKNov 02 2024
R-4.3-win-x86_64OKNov 02 2024
R-4.3-mac-x86_64OKNov 02 2024
R-4.3-mac-aarch64OKNov 02 2024

Exports:coef.cv.glmtlpcoef.glmtlpcv.glmtlpgen.binomial.datagen.gaussian.dataglmtlpplot.cv.glmtlpplot.glmtlppredict.cv.glmtlppredict.glmtlp

Dependencies:clicodetoolscolorspacedoParallelfansifarverforeachggplot2gluegtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr

An Introduction to glmtlp

Rendered fromglmtlp.Rmdusingknitr::rmarkdownon Nov 02 2024.

Last update: 2024-10-03
Started: 2021-10-15