The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
brglm: Bias Reduction in Binomial-Response Generalized Linear Models
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.
Documentation:
Downloads:
Reverse dependencies:
| Reverse depends: |
cnvGSA, glmvsd |
| Reverse imports: |
analogue, BradleyTerry2, brlrmr, MixedPsy |
| Reverse suggests: |
brglm2, enrichwith, mbrglm, optmatch, picante |
| Reverse enhances: |
prediction, stargazer, texreg |
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=brglm
to link to this page.
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.
Health stats visible at Monitor.
[aut, cre]