Fitting linear models and generalized linear models to large data sets by updating algorithms.
Version: | 0.3-2 |
Depends: | Matrix, MASS |
Imports: | methods, stats |
Published: | 2017-01-09 |
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 <emarco76 at libero.it> |
License: | GPL-2 | GPL-3 [expanded from: GPL] |
NeedsCompilation: | no |
Materials: | NEWS |
In views: | HighPerformanceComputing |
CRAN checks: | speedglm results |
Reference manual: | speedglm.pdf |
Package source: | speedglm_0.3-2.tar.gz |
Windows binaries: | r-devel: speedglm_0.3-2.zip, r-release: speedglm_0.3-2.zip, r-oldrel: speedglm_0.3-2.zip |
macOS binaries: | r-release: speedglm_0.3-2.tgz, r-oldrel: speedglm_0.3-2.tgz |
Old sources: | speedglm archive |
Reverse depends: | GWASinlps |
Reverse imports: | adapt4pv, allestimates, alpine, bigstep, btergm, chest, DMCFB, equSA, GEint, hit, LogisticDx, ltmle, PrInCE, smurf, survtmle, tensorregress |
Reverse suggests: | backbone, broom, disk.frame, dynamichazard, fbRanks, insight, mediation, SuperLearner |
Reverse enhances: | prediction, texreg |
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