dbglm: Generalised Linear Models by Subsampling and One-Step Polishing

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>.

Version: 1.0.0
Depends: R (≥ 2.10)
Imports: DBI, tidypredict, rlang, methods, tidyverse, dbplyr, vctrs, knitr, dplyr, purrr, tibble, tidyr, stringr
Suggests: RSQLite, duckdb, bigrquery, testthat (≥ 3.0.0)
Published: 2021-06-23
Author: Thomas Lumley [aut, cph], Shangqing Cao [ctb, cre]
Maintainer: Shangqing Cao <caoalbert at g.ucla.edu>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README
CRAN checks: dbglm results

Downloads:

Reference manual: dbglm.pdf
Package source: dbglm_1.0.0.tar.gz
Windows binaries: r-devel: dbglm_1.0.0.zip, r-release: dbglm_1.0.0.zip, r-oldrel: dbglm_1.0.0.zip
macOS binaries: r-release (arm64): dbglm_1.0.0.tgz, r-release (x86_64): dbglm_1.0.0.tgz, r-oldrel: dbglm_1.0.0.tgz

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