Type: Package
Package: subsampling
Title: Optimal Subsampling Methods for Statistical Models
Version: 0.1.1
Date: 2024-11-2
Authors@R: c(
    person("Qingkai", "Dong", , "qingkai.dong@uconn.edu", role = c("aut", "cre", "cph")),
    person("Yaqiong", "Yao", role = "aut"),
    person("Haiying", "Wang", role = "aut"),
    person("Qiang", "Zhang", role = "ctb"),
    person("Jun", "Yan", role = "ctb")
  )
Maintainer: Qingkai Dong <qingkai.dong@uconn.edu>
Description: 
    Balancing computational and statistical efficiency, subsampling techniques offer
    a practical solution for handling large-scale data analysis. Subsampling methods
    enhance statistical modeling for massive datasets by efficiently drawing
    representative subsamples from full dataset based on tailored sampling probabilities. These
    probabilities are optimized for specific goals, such as minimizing the variance
    of coefficient estimates or reducing prediction error.
License: GPL-3
URL: https://github.com/dqksnow/Subsampling
BugReports: https://github.com/dqksnow/Subsampling/issues
Imports: expm, nnet, quantreg, Rcpp (>= 1.0.12), stats, survey
Suggests: knitr, MASS, rmarkdown, tinytest
LinkingTo: Rcpp, RcppArmadillo
Config/testthat/edition: 3
Encoding: UTF-8
RoxygenNote: 7.3.2
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2024-11-02 23:30:06 UTC; qingkaidong
Author: Qingkai Dong [aut, cre, cph],
  Yaqiong Yao [aut],
  Haiying Wang [aut],
  Qiang Zhang [ctb],
  Jun Yan [ctb]
Repository: CRAN
Date/Publication: 2024-11-05 10:20:02 UTC
Built: R 4.5.2; x86_64-w64-mingw32; 2025-11-08 03:39:07 UTC; windows
Archs: x64
