Package: SGDinference
Type: Package
Title: Inference with Stochastic Gradient Descent
Version: 0.1.0
Authors@R: c(
    person("Sokbae", "Lee", email = "sl3841@columbia.edu", role = "aut"),
    person("Yuan", "Liao", email = "yuan.liao@rutgers.edu", role = "aut"),
    person("Myung Hwan", "Seo", email = "myunghseo@snu.ac.kr", role = "aut"),
    person("Youngki", "Shin", email = "shiny11@mcmaster.ca", role = c("aut", "cre")))
Description: Estimation and inference methods for large-scale mean and
        quantile regression models via stochastic (sub-)gradient
        descent (S-subGD) algorithms. The inference procedure handles
        cross-sectional data sequentially: (i) updating the parameter
        estimate with each incoming "new observation", (ii) aggregating
        it as a Polyak-Ruppert average, and (iii) computing an
        asymptotically pivotal statistic for inference through random
        scaling. The methodology used in the SGDinference package is
        described in detail in the following papers: (i) Lee, S., Liao,
        Y., Seo, M.H. and Shin, Y. (2022)
        <doi:10.1609/aaai.v36i7.20701> "Fast and robust online
        inference with stochastic gradient descent via random scaling".
        (ii) Lee, S., Liao, Y., Seo, M.H. and Shin, Y. (2023)
        <arXiv:2209.14502> "Fast Inference for Quantile Regression with
        Tens of Millions of Observations".
License: GPL-3
Imports: stats, Rcpp (>= 1.0.5)
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.2.3
Encoding: UTF-8
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), lmtest (>= 0.9),
        sandwich (>= 3.0), microbenchmark (>= 1.4), conquer (>= 1.3.3)
VignetteBuilder: knitr
Config/testthat/edition: 3
Depends: R (>= 3.5.0)
LazyData: true
URL: https://github.com/SGDinference-Lab/SGDinference/
BugReports: https://github.com/SGDinference-Lab/SGDinference/issues
Repository: https://sgdinference-lab.r-universe.dev
Date/Publication: 2023-11-15 00:50:43 UTC
RemoteUrl: https://github.com/sgdinference-lab/sgdinference
RemoteRef: HEAD
RemoteSha: a66700a9f704f70957520f7e0f496e5609775964
NeedsCompilation: yes
Packaged: 2026-06-22 09:14:10 UTC; root
Author: Sokbae Lee [aut],
  Yuan Liao [aut],
  Myung Hwan Seo [aut],
  Youngki Shin [aut, cre]
Maintainer: Youngki Shin <shiny11@mcmaster.ca>