brglm v0.7.1


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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.

Functions in brglm

Name Description
profileObjectives-brglm Objectives to be profiled
gethats Calculates the Leverages for a GLM through a C Routine
brglm.control Auxiliary for Controlling BRGLM Fitting
profile.brglm Calculate profiles for objects of class 'brglm'.
lizards Habitat Preferences of Lizards
brglm Bias reduction in Binomial-response GLMs
modifications Additive Modifications to the Binomial Responses and Totals for Use within `'
glm.control1 Auxiliary for Controlling BRGLM Fitting
plot.profile.brglm Plot methods for 'profile.brglm' objects
confint.brglm Computes confidence intervals of parameters for bias-reduced estimation
separation.detection Separation Identification.
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Type Package
License GPL (>= 2)
NeedsCompilation yes
Packaged 2020-10-11 23:41:22 UTC; yiannis
Repository CRAN
Date/Publication 2020-10-12 04:40:09 UTC
suggests MASS
depends profileModel , R (>= 2.6.0)

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