Bias reduction in binomial-response generalized linear models.
Description
Fit binomial-response generalized linear models using either a modified-score approach to bias reduction or maximum penalized likelihood where penalization is by Jeffreys invariant prior. Fitting takes place by iteratively fitting a local generalized linear models on a pseudo-data representation. 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 bias-reduced estimates.