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Fit generalized linear models with binomial responses using either an adjusted-score approach to bias reduction or maximum penalized likelihood where penalization is by Jeffreys invariant prior. These procedures return estimates with improved frequentist properties (bias, mean squared error) that are always finite even in cases where the maximum likelihood estimates are infinite (data separation). Fitting takes place by fitting generalized linear models on iteratively updated pseudo-data. The interface is essentially the same as 'glm'. More flexibility is provided by the fact that custom pseudo-data representations can be specified and used for model fitting. Functions are provided for the construction of confidence intervals for the reduced-bias estimates.
Version: | 0.7.2 |
Depends: | R (≥ 2.6.0), profileModel |
Suggests: | MASS |
Published: | 2021-04-22 |
DOI: | 10.32614/CRAN.package.brglm |
Author: | Ioannis Kosmidis |
Maintainer: | Ioannis Kosmidis <ioannis.kosmidis at warwick.ac.uk> |
BugReports: | https://github.com/ikosmidis/brglm/issues |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: | https://github.com/ikosmidis/brglm |
NeedsCompilation: | yes |
Citation: | brglm citation info |
In views: | Econometrics |
CRAN checks: | brglm results |
Reference manual: | brglm.pdf |
Package source: | brglm_0.7.2.tar.gz |
Windows binaries: | r-devel: brglm_0.7.2.zip, r-release: brglm_0.7.2.zip, r-oldrel: brglm_0.7.2.zip |
macOS binaries: | r-release (arm64): brglm_0.7.2.tgz, r-oldrel (arm64): brglm_0.7.2.tgz, r-release (x86_64): brglm_0.7.2.tgz, r-oldrel (x86_64): brglm_0.7.2.tgz |
Old sources: | brglm archive |
Reverse depends: | cnvGSA, glmvsd |
Reverse imports: | analogue, BradleyTerry2, brlrmr, MixedPsy |
Reverse suggests: | abn, brglm2, enrichwith, mbrglm, optmatch, picante |
Reverse enhances: | MuMIn, prediction, stargazer, texreg |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.