sgd: Stochastic Gradient Descent for Scalable Estimation
A fast and flexible set of tools for large scale estimation. It features many stochastic gradient methods, built-in models, visualization tools, automated hyperparameter tuning, model checking, interval estimation, and convergence diagnostics.
| Version: | 1.1.3 |
| Imports: | ggplot2,MASS, methods,Rcpp (≥ 0.11.3), stats |
| LinkingTo: | BH,bigmemory,Rcpp,RcppArmadillo |
| Suggests: | bigmemory,glmnet,gridExtra,R.rsp,testthat,microbenchmark |
| Published: | 2025-10-21 |
| DOI: | 10.32614/CRAN.package.sgd |
| Author: | Junhyung Lyle Kim [cre, aut], Dustin Tran [aut], Panos Toulis [aut], Tian Lian [ctb], Ye Kuang [ctb], Edoardo Airoldi [ctb] |
| Maintainer: | Junhyung Lyle Kim <jlylekim at gmail.com> |
| BugReports: | https://github.com/airoldilab/sgd/issues |
| License: | GPL-2 |
| URL: | https://github.com/airoldilab/sgd |
| NeedsCompilation: | yes |
| Materials: | README,NEWS |
| CRAN checks: | sgd results |
Documentation:
Downloads:
Linking:
Please use the canonical formhttps://CRAN.R-project.org/package=sgdto link to this page.