bracl objects with non-identifiable parameters.Work on output consistently from print() methods for summary.XYZ objects; estimator type is now printed and other fixes.
Enriched warning when algorithm does not converge with more informative text.
Documentation fixes and updates
brnb() allows fitting negative binomial regression models using implicit and explicit bias reduction methods. See vignettes for a case study.simulate() method for objects of class brmultinom and braclordinal_superiority() method to estimate Agresti and Kateri (2017)’s ordinal superiority measures, and compute bias corrections for those.Wald.ratios = TRUE in summary.brmultinom.vcov.bracl that would return an error if the "bracl" object was computed using bracl() with parallel = TRUE and one covariate.bracl() related to the handling or zero weights that could result in hard-to-traceback errors.bracl() that could cause errors in fits with one covariate.brglmFit() iteration returns last estimates that worked if iteration fails.confint() was not returning anything when applied to objects of class brmultinom.control glm(). argument was specified using the output from brglmControl() or brglm_control().check_aliasing option in brglmControl() to tell brglm_fit() to skip (check_aliasing = TRUE) or not (check_aliasing = FALSE) rank deficiency checks (through a QR decomposition of the model matrix), saving some computational effort.NA coefficients when brglmFit() was called with a vector x or an x with no column names.confint method for brmulitnom objectsvcov.brglmFit() now uses vcov.summary.glm() and supports the complete argument for controlling whether the variance covariance matrix should include rows and columns for aliased parameters.detect_sepration() and check_infinite_estimates(), which will be removed from brglm2 at version 0.8. New versions of detect_sepration() and check_infinite_estimates() are now maintained in the detectseparation R package.print.summary() for brmultinom and bracl objects.detect_separation() now handles one-column model matrices correctly.brglmFit() can now do maximum penalized likelihood with powers of the Jeffreys prior as penalty (type = "MPL_Jeffreys) for all supported generalized linear models. See the help files of brglmControl() and brglmFit() for details.?brglmFit.print.brmultinom() is now exported, so bracl and brmultinom objects print correctly.response_adjustment argument in brglmControl() to allow for more fine-tuning of the starting values when brglmFit() is called with start = NULL.brglmControl().brglmFit() now works as expected with custom link functions (mean and median bias reduction).brglmFit() respects the specification of the transformation argument in brglmControl().brglmFit().quasi(), quasibinomial() and quasibinomial() families and documentation update.bracl() for fitting adjacent category logit models for ordinal responses using maximum likelihood, mean bias reduction, and median bias reduction and associated methods (logLik, summary and so on).predict() methods for brmultinom and bracl objects. Added residuals() methods for brmultinom and bracl objects (residuals of the equivalent Poisson log-linear model)mis() link functions for accounting for misclassification in binomial response models (Neuhaus, 1999, Biometrika).summary() method for brmultinom objects.NA dispersion for models with 0 df resid.type = AS_mixed as an option to use mean-bias reducing score functions for the regression parameters and median-bias reducing score functions for the dispersion in models with unknown dispersion.check_infinite_estimates() now accepts brmultinom objects.singular.ok argument to brglmFit() and detect_separation() methods in line with the update of glm.fit().brglm_control().brglmControl() is now exported.slowit did nothing; now included in iteration.detect_separation() method for the glm() function can be used to check for separation in binomial response settings without fitting the model. This relies on a port of Kjell Konis’ safeBinaryRegression:::separator() function (see ?detect_separation).type = "AS_median".brglmFit(), brglm_fit(), detectSeparation(), detect_separation(), brglm_control(), brglmControl(), detectSeparationControl(), detect_separation_control(), checkInfiniteEstimates(), check_infinite_estimates()).cho2inv().