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NeEDS4BigData

1.0.1Package record

New Experimental Design Based Subsampling Methods for Big Data

0packages depend
2.7Kdownloads / year
90.4%test coverage
12/13flavors OK

Overview

About

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.

Install

Health

CRAN checks
1ERROR12OK
Check messages
ERRORexamplesr-devel-linux-x86_64-debian-gcc
Running examples in ‘NeEDS4BigData-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: modelMissLinSub
> ### Title: Subsampling under linear regression for a potentially
> ###   misspecified model
> ### Aliases: modelMissLinSub
> 
> ### ** Examples
> 
> Beta <- c(-1, 0.75, 0.75, 1); Var_Epsilon <- 0.5;
> family <- "linear"; N <- 500
> X_1 <- replicate(2, stats::runif(n = N, min = -1, max = 1))
> 
> Temp <- Rfast::rowprods(X_1)
> Misspecification <- (Temp - mean(Temp)) / sqrt(mean(Temp^2) - mean(Temp)^2)
> X_Data <- cbind(X0 = 1, X_1)
> 
> Full_Data <- GenModelMissGLMdata(N, X_Data, Misspecification, Beta, Var_Epsilon, family)
> r0 <- 40; rf <- rep(10 * c(8, 12), 25)
> Original_Data <- Full_Data$Complete_Data[, -ncol(Full_Data$Complete_Data)]
> 
> Results <- modelMissLinSub(r0 = r0, rf = rf,
+                            Y = as.matrix(Original_Data[, 1]),
+                            X = as.matrix(Original_Data[, -1]),
+                            N = N, Alpha = 10, proportion = 0.5)
50% or >=50% of the big data is used to help find AMSE for the subsamples, 
this could take some time.
Error in a$specials[[i]] : subscript out of bounds
Calls: modelMissLinSub ... predict.glm -> predict.lm -> delete.response -> off
Execution halted
Examples with CPU (user + system) or elapsed time > 5s
                 user system elapsed
ALoptimalGLMSub 3.878  0.551   6.044
ERRORtestsr-devel-linux-x86_64-debian-gcc
Running ‘spelling.R’ [0s/0s]
  Running ‘testthat.R’ [12s/16s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > # This file is part of the standard setup for testthat.
  > # It is recommended that you do not modify it.
  > #
  > # Where should you do additional test configuration?
  > # Learn more about the roles of various files in:
  > # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
  > # * https://testthat.r-lib.org/articles/special-files.html
  > 
  > library(testthat)
  > library(NeEDS4BigData)
  > 
  > test_check("NeEDS4BigData")
  Saving _problems/test-modelMissLinSub-15.R
  Saving _problems/test-modelMissLogSub-14.R
  Saving _problems/test-modelMissPoiSub-14.R
  Saving _problems/test-plot_AMSE-15.R
  [ FAIL 4 | WARN 0 | SKIP 0 | PASS 283 ]
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test-modelMissLinSub.R:12:1'): (code run outside of `test_that()`) ──
  <subscriptOutOfBoundsError/error
...[truncated]...
Gam(...)
    8.       └─stats::predict.glm(...)
    9.         └─stats::predict.lm(...)
   10.           └─stats::delete.response(tt)
   11.             └─stats (local) off(a$specials[[i]])
  ── Error ('test-plot_AMSE.R:12:1'): (code run outside of `test_that()`) ────────
  <subscriptOutOfBoundsError/error/condition>
  Error in `a$specials[[i]]`: subscript out of bounds
  Backtrace:
       ▆
    1. ├─base::suppressMessages(...) at test-plot_AMSE.R:12:1
    2. │ └─base::withCallingHandlers(...)
    3. ├─base::suppressWarnings(...)
    4. │ └─base::withCallingHandlers(...)
    5. └─NeEDS4BigData::modelMissLinSub(...)
    6.   └─gam::predict.Gam(fit_GAM, newdata = data.frame(X))
    7.     └─gam::newdata.predict.Gam(...)
    8.       └─stats::predict.glm(...)
    9.         └─stats::predict.lm(...)
   10.           └─stats::delete.response(tt)
   11.             └─stats (local) off(a$specials[[i]])
  
  [ FAIL 4 | WARN 0 | SKIP 0 | PASS 283 ]
  Error:
  ! Test failures.
  Execution halted

CRAN check page ↗

Slowest check: 6.7 min · r-oldrel-macos-x86_64
Status changes
  • ERROR12 OK, 1 ERROR2026-10-24
  • OK13 OK2026-08-12
  • ERROR12 OK, 1 ERROR2026-08-09
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
Show 10 earlier changesHide 10 earlier changes
  • OK13 OK2026-06-20
  • ERROR12 OK, 1 ERROR2026-06-18
  • OK13 OK2026-05-24
  • ERROR12 OK, 1 ERROR2026-05-22
  • OK12 OK2026-04-25
  • NOTE11 OK, 3 NOTE2026-04-15
  • ERROR10 OK, 3 NOTE, 1 ERROR2026-04-11
  • NOTE11 OK, 3 NOTE2026-03-25
  • ERROR11 OK, 2 NOTE, 1 ERROR2026-03-22
  • NOTE11 OK, 3 NOTE2026-03-10
Advisories

none known

Documentation

In release 1.0.1
README· In the repository, left out of the releaseVignettes· In the repository, left out of the releaseNEWS· In the repository, left out of the releaseCitation fileNoWebsiteYes · pkgdown
Help pages
18
Examples that run
100%16 run in a plain check
Exported functions with examples
87%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
78% with a bibliography file

Downloads

2.7K
CRAN downloads in the past year
Rank #17,648 · ~7/day · ~225/mo
Daily download trend is not available in this view yet.
27930 days
73290 days
2.7K1 year
Compare downloads with other packages →
Also on132 r2u4 autocran

Repository

3Stars
0Forks
0Open issues
0Open PRs
0Releases
72Commits
1Commit identities
big-datacranexperimental-designsubsampling
72 commits · Last activity 2025-10-18 · 0% stars, 30d
Responsiveness
not measured

Stars over time

2025-10-23 · 22026-07-07 · 3
PracticesBeta

10 development-tooling and community-health practices detected across 6 families in the upstream repository

Checks run against github.com/amalan-constat/needs4bigdata on 2026-10-21.

Governance and community (1)
Code of conduct
Docs source (3)
README.Rmdpkgdown

GitHub Pages site last deployed 2025-10-18

Coverage (1)
Coverage reporting (Codecov)
Reproducibility and dev environment (2)
renvdata-raw/
Show all practicesHide 2 practices
CRAN release process (2)
cran-comments.mdCRAN-SUBMISSION
Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies
22 external dependencies (excludes base and recommended)

Installing NeEDS4BigData adds 47 packages (25 with compiled code, 55 MB of source tarballs). Heaviest: BH 14 MB, stringi 11 MB, ggplot2 6.0 MB.

Depends (1)
R >= 4.1.0
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (1)
Author, Maintainer since 1.0.1 (2025)
Releases (1)
  • R
    R 4.6.0 released · 2026-04-24
  • 1.0.1Latest
    2025-10-22 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2025-10-22
Total releases
1 / 1 yrs
License
MIT + file LICENSE OSI
Minimum R
≥ 4.1.0
Bundled data
6.7 MB / 3 files
Download size
7.5 MB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("NeEDS4BigData")
Mahendran, A. (2025). NeEDS4BigData: New Experimental Design Based Subsampling Methods for Big Data (Version 1.0.1) [Computer software]. https://doi.org/10.32614/CRAN.package.NeEDS4BigData

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for NeEDS4BigData version 1.0.1 [Data set]. HJJB, LLC. Data release v2026-10-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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