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: 1.1.2
Imports: ggplot2, MASS, methods, Rcpp (≥ 0.11.3), stats
LinkingTo: BH, bigmemory, Rcpp, RcppArmadillo
Suggests: bigmemory, glmnet, gridExtra, R.rsp, testthat
Published: 2024-01-31
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>
License: GPL-2
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_1.1.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): sgd_1.1.2.tgz, r-oldrel (arm64): sgd_1.1.2.tgz, r-release (x86_64): sgd_1.1.2.tgz, r-oldrel (x86_64): sgd_1.1.2.tgz
Old sources: sgd archive


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