Package: biglasso 1.6.1
biglasso: Extending Lasso Model Fitting to Big Data
Extend lasso and elastic-net model fitting for large data sets that cannot be loaded into memory. Designed to be more memory- and computation-efficient than existing lasso-fitting packages like 'glmnet' and 'ncvreg', thus allowing the user to analyze big data with limited RAM <doi:10.32614/RJ-2021-001>.
Authors:
biglasso_1.6.1.tar.gz
biglasso_1.6.1.tar.gz(r-4.5-noble)biglasso_1.6.1.tar.gz(r-4.4-noble)
biglasso_1.6.1.tgz(r-4.4-emscripten)biglasso_1.6.1.tgz(r-4.3-emscripten)
biglasso.pdf |biglasso.html✨
biglasso/json (API)
NEWS
# Install 'biglasso' in R: |
install.packages('biglasso', repos = 'https://cloud.r-project.org') |
Bug tracker:https://github.com/pbreheny/biglasso/issues
Pkgdown site:https://pbreheny.github.io
- colon - Gene expression data from colon-cancer patients
Last updated 2 days agofrom:0957868de2. Checks:3 OK. Indexed: no.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Mar 05 2025 |
R-4.5-linux-x86_64 | OK | Mar 05 2025 |
R-4.4-linux-x86_64 | OK | Mar 05 2025 |
Exports:biglassobiglasso_fitbiglasso_pathcv.biglassosetupX
Dependencies:BHbigmemorybigmemory.srilatticeMatrixncvregRcppRcppArmadillouuid
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Extending Lasso Model Fitting to Big Data | biglasso-package |
Fit lasso penalized regression path for big data | biglasso |
Direct interface to biglasso fitting, no preprocessing | biglasso_fit |
Direct interface to biglasso fitting, no preprocessing, path version | biglasso_path |
Gene expression data from colon-cancer patients | colon |
Cross-validation for biglasso | cv.biglasso |
Plot coefficients from a "biglasso" object | plot.biglasso |
Plots the cross-validation curve from a "cv.biglasso" object | plot.cv.biglasso |
Plot coefficients from a "mbiglasso" object | plot.mbiglasso |
Model predictions based on a fitted 'biglasso' object | coef.biglasso coef.mbiglasso predict.biglasso predict.mbiglasso |
Model predictions based on a fitted 'cv.biglasso()' object | coef.cv.biglasso predict.cv.biglasso |
Set up design matrix X by reading data from big data file | setupX |
Summarizing inferences based on cross-validation | print.summary.cv.biglasso summary.cv.biglasso |