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 |
| Imports: | ggplot2, MASS, methods, Rcpp (≥ 0.11.3) |
| LinkingTo: | BH, bigmemory, Rcpp, RcppArmadillo |
| Suggests: | bigmemory, gridExtra, R.rsp, testthat |
| Published: | 2016-01-05 |
| Author: | Dustin Tran [aut, cre], Panos Toulis [aut], Tian Lian [ctb], Ye Kuang [ctb], Edoardo Airoldi [ctb] |
| Maintainer: | Dustin Tran <dustin at cs.columbia.edu> |
| BugReports: | https://github.com/airoldilab/sgd/issues |
| License: | GPL-2 |
| URL: | https://github.com/airoldilab/sgd |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | sgd results |
| Reference manual: | sgd.pdf |
| Vignettes: |
Stochastic gradient decent methods for estimation with large data sets |
| Package source: | sgd_1.1.tar.gz |
| Windows binaries: | r-devel: sgd_1.1.zip, r-release: sgd_1.1.zip, r-oldrel: sgd_1.1.zip |
| OS X Mavericks binaries: | r-release: sgd_1.1.tgz, r-oldrel: sgd_1.1.tgz |
| Old sources: | sgd archive |
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