Convergence of the brglm_fit iterations is now determined if the L^Inf norm of the step size (rather than the L^1 as it was previously) of the quasi-Fisher scoring procedure is less thanepsilon (see ?brglm_control for the definition of epsilon). This is more natural as epsilonthen determines directly the precision of the reported estimates and does not depend on their number.
brglm_control() now checks that the supplied value of max_step_factor is numeric and greater or equal to1. If not, then it is set to the default value of12.
Vignette updates
brglm2 0.9.1
Improvements, updates and additions
Added the enzymes and hepatitis data sets (from the pmlr) to support examples and tests.
brglm2 0.9.0
New functionality
The expo() method for brglmFit andglm objects estimates the exponential of parameters of generalized linear models with maximum likelihood or various mean and median bias reduction methods (see ?expo for details). Theexpo() method is particularly useful for computing (corrected) estimates of the multiplicative impact of a unit increase on a covariate on the mean of a Poisson log-linear model (family = poisson("log") in glm()) while adjusting for other covariates, the odds ratio associated with a unit increase on a covariate in a logistic regression model (family = binomial("logit") in glm()) while adjusting for other covariates, the relative risk associated with a unit increase on a covariate in a relative risk regression model (family = binomial("log") in glm()) while adjusting for other covariates, among others.
Bug fixes
Fixed a bug where the dispersion in the resulting object would not be transformed even if transformation != "identity" whentype is ML or AS_median orAS_mixed.
Moved documentation to markdown markup through roxygen2.
New vignette titled “Estimating the exponential of regression parameters using brglm2”, to demonstrate theexpo() method.
Various documentation fixes.
brglm2 0.8.2
Improvements, updates and additions
Housekeeping.
Removed lpSolveAPI from imports.
brglm2 0.8.1
Bug fixes
Fixed a bug when predicting from bracl objects with non-identifiable parameters.
Improvements, updates and additions
Work on output consistently from print() methods forsummary.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
brglm2 0.8.0
New functionality
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 classbrmultinom and bracl
ordinal_superiority() method to estimate Agresti and Kateri (2017)’s ordinal superiority measures, and compute bias corrections for those.
Bug fixes
Fixed a bug that would return an error whenWald.ratios = TRUE in summary.brmultinom.
Fixed bug in vcov.bracl that would return an error if the "bracl" object was computed using bracl()with parallel = TRUE and one covariate.
Fixed a bug in bracl() related to the handling or zero weights that could result in hard-to-traceback errors.
Fixed a bug in bracl() that could cause errors in fits with one covariate.
brglmFit() iteration returns last estimates that worked if iteration fails.
Improvements, updates and additions
Documentation and example updates.
brglm2 0.7.1
Bug fixes
Fixed bug where confint() was not returning anything when applied to objects of class brmultinom.
Fixed bug where and error could result when the controlglm(). argument was specified using the output frombrglmControl() or brglm_control().
New functionality
added check_aliasing option inbrglmControl() 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.
Improvements, updates and additions
updated DOI links in documentation and some http -> https fixes.
brglm2 0.7.0
Bug fixes
Fixed bug that resulted in NA coefficients whenbrglmFit() was called with a vector x or anx with no column names.
vcov.brglmFit() now usesvcov.summary.glm() and supports the completeargument for controlling whether the variance covariance matrix should include rows and columns for aliased parameters.
Deprecated detect_sepration() andcheck_infinite_estimates(), which will be removed frombrglm2 at version 0.8. New versions ofdetect_sepration() andcheck_infinite_estimates() are now maintained in the detectseparationR package.
Fixed typos in NEWS.
brglm2 0.6.1
Bug fixes
Fixed bug in AIC reported by print.summary() forbrmultinom and bracl objects.
detect_separation() now handles one-column model matrices correctly.
Improvements, updates and additions
Documentation improvements and typo fixes.
brglm2 0.6
New functionality
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() andbrglmFit() for details.
Improvements, updates and additions
Documentation updates and improvements.
Updated vignettes to include maximum penalized likelihood with powers of the Jeffreys prior as penalty.
New examples in ?brglmFit.
brglm2 0.5.2
Bug fixes
print.brmultinom() is now exported, sobracl and brmultinom objects print correctly.
New functionality
Added response_adjustment argument inbrglmControl() to allow for more fine-tuning of the starting values when brglmFit() is called withstart = NULL.
Improvements, updates and additions
Documentation updates and improvements.
Added Kosmidis et al (2019) in the description file.
Added tests for brglmControl().
brglm2 0.5.1
Improvements, updates and additions
Fixed typos in vignettes and documentation.
Added ORCHID for Ioannis Kosmidis in DESCRIPTION.
brglm2 0.5.0
Bug fixes
brglmFit() now works as expected with custom link functions (mean and median bias reduction).
brglmFit() respects the specification of the transformation argument in brglmControl().
Fixed bug in the computation of the QR decomposition under aliasing in brglmFit().
Other minor bug fixes and performance improvements.
Protection against use of quasi(),quasibinomial() and quasibinomial() families and documentation update.
New functionality
Added 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).
Added predict() methods for brmultinom andbracl objects. Added residuals() methods forbrmultinom and bracl objects (residuals of the equivalent Poisson log-linear model)
Added the mis() link functions for accounting for misclassification in binomial response models (Neuhaus, 1999, Biometrika).
Removed warning about observations with non-positive weights from brmultinom.
Updated email address for Ioannis Kosmidis in brglmFit.
Bug fixes
brmultinom returns a fitted values matrix that respects the dimension of data.
Fixed bug on condition for NA dispersion for models with 0 df resid.
brglm2 0.1.7
Improvements, updates and additions
Eliminated errors from markdown chunks in multinomial vignette.
brglm2 0.1.6
Bug fixes
Compatibility with new version of enrichwith.
Improvements, updates and additions
New email for Ioannis Kosmidis.
brglm2 0.1.5
Bug fixes
New functionality
Added type = AS_mixed as an option to usemean-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 acceptsbrmultinom objects.
Added singular.ok argument to brglmFit()and detect_separation() methods in line with the update ofglm.fit().
Improvements, updates and additions
less strict tolerance in brglm_control().
Updates to help files.
Fixed typos in iteration vignette.
Added URL and bugreports in Description.
Added new tests.
brglm2 0.1.4
Bug fixes
brglmControl() is now exported.
slowit did nothing; now included in iteration.
New functionality
The detect_separation() method for theglm() 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).