speedglm: Fitting Linear and Generalized Linear Models to Large Data Sets

Fitting linear models and generalized linear models to large data sets by updating algorithms, according to the method described in Enea (2009, ISBN: 9788861294257).

Version:	0.3-5
Depends:	Matrix, MASS, biglm
Imports:	methods, stats
Published:	2023-05-06
DOI:	10.32614/CRAN.package.speedglm
Author:	Marco Enea [aut, cre], Ronen Meiri [ctb] (on behalf of DMWay Analytics LTD), Tomer Kalimi [ctb] (on behalf of DMWay Analytics LTD)
Maintainer:	Marco Enea <marco.enea at unipa.it>
License:	GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation:	no
Materials:	NEWS
CRAN checks:	speedglm results

Documentation:

Reference manual:

speedglm.pdf

Downloads:

Package source:	speedglm_0.3-5.tar.gz
Windows binaries:	r-devel: speedglm_0.3-5.zip, r-release: speedglm_0.3-5.zip, r-oldrel: speedglm_0.3-5.zip
macOS binaries:	r-release (arm64): speedglm_0.3-5.tgz, r-oldrel (arm64): speedglm_0.3-5.tgz, r-release (x86_64): speedglm_0.3-5.tgz, r-oldrel (x86_64): speedglm_0.3-5.tgz

Reverse dependencies:

Reverse imports:	adapt4pv, bigstep, DMCFB, drglm, EMJMCMC, EventPointer, PrInCE, scDiagnostics
Reverse suggests:	broom, btergm, ggeffects, insight, marginaleffects, mediation, parglm, SuperLearner, superMICE
Reverse enhances:	fastlogitME, prediction, texreg

Linking:

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