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brglm  

Bias Reduction in Binomial-Response Generalized Linear Models
View on CRAN: Click here


Download and install brglm package within the R console
Install from CRAN:
install.packages("brglm")

Install from Github:
library("remotes")
install_github("cran/brglm")

Install by package version:
library("remotes")
install_version("brglm", "0.7.2")



Attach the package and use:
library("brglm")
Maintained by
Ioannis Kosmidis
[Scholar Profile | Author Map]
First Published: 2008-02-25
Latest Update: 2021-04-22
Description:
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.
How to cite:
Ioannis Kosmidis (2008). brglm: Bias Reduction in Binomial-Response Generalized Linear Models. R package version 0.7.2, https://cran.r-project.org/web/packages/brglm. Accessed 07 Apr. 2025.
Previous versions and publish date:
0.5-2 (2008-02-25 08:43), 0.5-3 (2008-04-10 09:16), 0.5-4 (2008-11-26 09:47), 0.5-5 (2010-06-22 10:30), 0.5-6 (2011-08-17 07:30), 0.5-7 (2012-08-24 10:35), 0.5-8 (2013-08-08 01:27), 0.5-9 (2013-11-08 11:39), 0.6.1 (2017-06-29 07:56), 0.6.2 (2019-04-02 19:40), 0.7.1 (2020-10-12 06:40)
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Complete documentation for brglm
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