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brglm2 0.9.2

Improvements, updates and additions

  • 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 than epsilon (see ?brglm_control for the definition of epsilon). This is more natural as epsilon then 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 to 1. If not, then it is set to the default value of 12.

  • 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 and glm 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). The expo() 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" when type is ML or AS_median or AS_mixed.

Improvements, updates and additions

  • Moved unit tests to tinytest.

  • Moved documentation to markdown markup through roxygen2.

  • New vignette titled "Estimating the exponential of regression parameters using brglm2", to demonstrate the expo() 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 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

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 class brmultinom 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 when Wald.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 control glm(). argument was specified using the output from brglmControl() or brglm_control().

New functionality

  • added 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.

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 when brglmFit() was called with a vector x or an x with no column names.

New functionality

  • confint method for brmulitnom objects

Improvements, updates and additions

brglm2 0.6.2

Improvements, updates and additions

  • vcov.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.
  • Deprecated 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.
  • Fixed typos in NEWS.

brglm2 0.6.1

Bug fixes

  • Fixed bug in AIC reported by print.summary() for brmultinom 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() and brglmFit() 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, so bracl and brmultinom objects print correctly.

New functionality

  • Added response_adjustment argument in brglmControl() to allow for more fine-tuning of the starting values when brglmFit() is called with start = 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 and bracl objects. Added residuals() methods for brmultinom 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).

Improvements, updates and additions

brglm2 0.1.8

Improvements, updates and additions

  • Improved documentation examples.
  • 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 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.
  • Added singular.ok argument to brglmFit() and detect_separation() methods in line with the update of glm.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 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).
  • brglm2 provides estimation via median-bias reducing score functions with type = "AS_median".
  • brglm2 provides camel and underscored aliases for basic methods (brglmFit(), brglm_fit(), detectSeparation(), detect_separation(), brglm_control(), brglmControl(), detectSeparationControl(), detect_separation_control(), checkInfiniteEstimates(), check_infinite_estimates()).

Improvements, updates and additions

  • Minor enhancements in the codebase.
  • The inverse expected information matrix is computed internally using cho2inv().
  • Internal changes to have more meaningful variable names.
  • Renamed detect_infinite* to check_infinite.

brglm2 0.1.3

Improvements, updates and additions

  • Fixed typo in $f_{Y_i}(y)$ in iteration vignette (thanks to Eugene Clovis Kenne Pagui for spotting),

brglm2 0.1.2

  • First release.