Generalised Linear Models by Subsampling and One-Step Polishing
Overview
Fast fitting of generalised linear models on moderately large datasets, by taking an initial sample, fitting in memory, then evaluating the score function for the full data in the database. Thomas Lumley doi:10.1080/10618600.2019.1610312.
Install
Health
NOTEdependencies in R coder-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Namespaces in Imports field not imported from: ‘knitr’ ‘tidyverse’ ‘vctrs’ All declared Imports should be used.
- NOTE11 OK, 2 NOTE2026-06-09
- ERROR10 OK, 2 NOTE, 1 ERROR2026-06-08
- NOTE12 OK, 2 NOTE2026-03-10
Documentation
- Help pages
- 2
- Examples that run
- no examples
- Exported functions with examples
- 0%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 50%
Downloads
Dependencies
Installing dbglm adds 101 packages (49 with compiled code, 67 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.
Code & Tests
Datasets
People & History
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- 1.0.0Latest2021-06-23 · current release
- RR 4.1.0 released · 2021-05-18
Package metadata
- First published
- 2021-06-23
- Total releases
- 1 / 5 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 2.10
- Bundled data
- 33 KB / 1 file
- Download size
- 44 KB
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