NeEDS4BigData: New Experimental Design Based Subsampling Methods for Big Data

Subsampling methods for big data under different models and assumptions. Starting with linear regression and leading to Generalised Linear Models, softmax regression, and quantile regression. Specifically, the model-robust subsampling method proposed in Mahendran, A., Thompson, H., and McGree, J. M. (2023) <doi:10.1007/s00362-023-01446-9>, where multiple models can describe the big data, and the subsampling framework for potentially misspecified Generalised Linear Models in Mahendran, A., Thompson, H., and McGree, J. M. (2025) <doi:10.48550/arXiv.2510.05902>.

Version:	1.0.1
Depends:	R (≥ 4.1.0)
Imports:	dplyr, foreach, gam, ggh4x, ggplot2, ggridges, matrixStats, mvnfast, psych, Rdpack, Rfast, rlang, stats, tidyr
Suggests:	doParallel, ggpubr, kableExtra, knitr, parallel, rmarkdown, spelling, testthat, vctrs, pillar
Published:	2025-10-22
DOI:	10.32614/CRAN.package.NeEDS4BigData (may not be active yet)
Author:	Amalan Mahendran [aut, cre]
Maintainer:	Amalan Mahendran <amalan0595 at gmail.com>
BugReports:	https://github.com/Amalan-ConStat/NeEDS4BigData/issues
License:	MIT + file LICENSE
URL:	https://github.com/Amalan-ConStat/NeEDS4BigData,https://amalan-constat.github.io/NeEDS4BigData/index.html
NeedsCompilation:	no
Language:	en-GB
CRAN checks:	NeEDS4BigData results

Documentation:

Reference manual:

NeEDS4BigData.html , NeEDS4BigData.pdf

Downloads:

Package source:	NeEDS4BigData_1.0.1.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): NeEDS4BigData_1.0.1.tgz, r-oldrel (arm64): NeEDS4BigData_1.0.1.tgz, r-release (x86_64): NeEDS4BigData_1.0.1.tgz, r-oldrel (x86_64): NeEDS4BigData_1.0.1.tgz

Linking:

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