Package: sgd 1.1.3

Junhyung Lyle Kim

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.

Authors:Junhyung Lyle Kim [cre, aut], Dustin Tran [aut], Panos Toulis [aut], Tian Lian [ctb], Ye Kuang [ctb], Edoardo Airoldi [ctb]

sgd_1.1.3.tar.gz
sgd_1.1.3.tar.gz(r-4.7-arm64)sgd_1.1.3.tar.gz(r-4.7-x86_64)sgd_1.1.3.tar.gz(r-4.6-arm64)sgd_1.1.3.tar.gz(r-4.6-x86_64)
sgd_1.1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
sgd/json (API)
NEWS

# Install 'sgd' in R:
install.packages('sgd', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/airoldilab/sgd/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • winequality - Wine quality data of white wine samples from Portugal

On CRAN:

Conda:

openblascpp

3.89 score 78 scripts 294 downloads 2 mentions 2 exports 24 dependencies

Last updated from:a06efdc999. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK145
linux-devel-x86_64OK149
source / vignettesOK202
linux-release-arm64OK148
linux-release-x86_64OK153
wasm-releaseOK133

Exports:predict_allsgd

Dependencies:BHbigmemorybigmemory.sriclicpp11farverggplot2gluegtableisobandlabelinglifecycleMASSR6RColorBrewerRcppRcppArmadillorlangS7scalesuuidvctrsviridisLitewithr

Stochastic gradient decent methods for estimation with large data sets

Rendered fromsgd-jss.pdf.asisusingR.rsp::asison Jun 18 2026.

Last update: 2015-09-23
Started: 2015-09-23