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bigReg

0.1.5

Generalized Linear Models (GLM) for Large Data Sets

0packages depend
1.3Kdownloads / year
test coverage
8/10checks pass

Overview

About
Maintained by Chibisi Chima-OkerekeFirst published 2016-07-252 releasesCRAN page ↗

Allows the user to carry out GLM on very large data sets. Data can be created using the data_frame() function and appended to the object with object$append(data); data_frame and data_matrix objects are available that allow the user to store large data on disk. The data is stored as doubles in binary format and any character columns are transformed to factors and then stored as numeric (binary) data while a look-up table is stored in a separate .meta_data file in the same folder. The data is stored in blocks and GLM regression algorithm is modified and carries out a MapReduce- like algorithm to fit the model. The functions bglm(), and summary() and bglm_predict() are available for creating and post-processing of models. The library requires Armadillo installed on your system. It may not function on windows since multi-core processing is done using mclapply() which forks R on Unix/Linux type operating systems.

Install

Health

CRAN checks
2NOTE8OK
Failing flavors
  • NOTE r-devel-linux-x86_64-debian-clang
  • NOTE r-devel-linux-x86_64-debian-gcc
Slowest check: 1.4 min · r-devel-linux-x86_64-debian-clang
Code health
None
Tests · ratio 0.00
not tracked
Coverage
6
Dependencies · direct
Check history
  • NOTE2026-03-10
    9 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMENoVignettesNopkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
not tracked
Return-value docs
not tracked
References docs
2%

Downloads

1.3K
CRAN downloads in the past year
Rank #23,846 · ~4/day · ~111/mo
Daily download trend is not available in this view yet.
13330 days
38190 days
1.3K1 year
Compare downloads with other packages →
Also on376 r2u52 autocran

Dependencies

Declared dependencies
4 external dependencies (excludes base and recommended)
Depends (7)
R >= 3.2.0RcppparallelmethodsstatsuuidMASS
Imports (0)
none
LinkingTo (2)
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

Datasets

People & History

People (0)

Author records are not tracked yet for this package.

Listed in earlier versions (1)
no longer listed · 0.1.2 to 0.1.5
Package Timeline

2 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • 0.1.5Latest
    2023-12-11 · current release · diff ↗
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • R
    R 4.0.0 released · 2020-04-24
  • R
    R 3.6.0 released · 2019-04-26
  • R
    R 3.5.0 released · 2018-04-23
  • R
    R 3.4.0 released · 2017-04-21
  • 0.1.2
    2016-07-25
  • R
    R 3.3.0 released · 2016-05-03

Package metadata

First published
2016-07-25
Total releases
2 / 10 yrs
License
GPL (>= 2) OSI
Minimum R
≥ 3.2.0
Bundled data
0.4 KB / 1 file
Download size
30 KB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("bigReg")

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 bigReg version 0.1.5 [Data set]. HJJB, LLC. Data release v2026-08-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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