Package: biglasso 1.6.0
Patrick Breheny
biglasso: Extending Lasso Model Fitting to Big Data
Extend lasso and elastic-net model fitting for ultra high-dimensional, multi-gigabyte 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 analysis even on an ordinary laptop.
Authors:
biglasso_1.6.0.tar.gz
biglasso_1.6.0.tar.gz(r-4.5-noble)biglasso_1.6.0.tar.gz(r-4.4-noble)
biglasso_1.6.0.tgz(r-4.4-emscripten)biglasso_1.6.0.tgz(r-4.3-emscripten)
biglasso.pdf |biglasso.html✨
biglasso/json (API)
NEWS
| # Install 'biglasso' in R: |
| install.packages('biglasso', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/pbreheny/biglasso/issues
- colon - Gene expression data from colon-cancer patients
Last updated 7 months agofrom:fb06d11b16. Checks:OK: 1 NOTE: 1. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 31 2024 |
| R-4.5-linux-x86_64 | NOTE | Oct 31 2024 |
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 |
