brglm2

Bias Reduction in Generalized Linear Models

CRAN Package

Estimation and inference from generalized linear models based on various methods for bias reduction and maximum penalized likelihood with powers of the Jeffreys prior as penalty. The 'brglmFit' fitting method can achieve reduction of estimation bias by solving either the mean bias-reducing adjusted score equations in Firth (1993) <doi:10.1093/biomet/80.1.27> and Kosmidis and Firth (2009) <doi:10.1093/biomet/asp055>, or the median bias-reduction adjusted score equations in Kenne et al. (2017) <doi:10.1093/biomet/asx046>, or through the direct subtraction of an estimate of the bias of the maximum likelihood estimator from the maximum likelihood estimates as in Cordeiro and McCullagh (1991) <https://www.jstor.org/stable/2345592>. See Kosmidis et al (2020) <doi:10.1007/s11222-019-09860-6> for more details. Estimation in all cases takes place via a quasi Fisher scoring algorithm, and S3 methods for the construction of of confidence intervals for the reduced-bias estimates are provided. In the special case of generalized linear models for binomial and multinomial responses (both ordinal and nominal), the adjusted score approaches to mean and media bias reduction have been found to return estimates with improved frequentist properties, that are also always finite, even in cases where the maximum likelihood estimates are infinite (e.g. complete and quasi-complete separation; see Kosmidis and Firth, 2020 <doi:10.1093/biomet/asaa052>, for a proof for mean bias reduction in logistic regression).


Documentation


Team


Insights

Last 30 days

This package has been downloaded 5,327 times in the last 30 days. A solid achievement! Enough downloads to get noticed at department meetings. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 161 times.

Sun
Mon
Tue
Wed
Thu
Fri
Sat
0 downloadsMar 2, 2025
0 downloadsMar 3, 2025
260 downloadsMar 4, 2025
292 downloadsMar 5, 2025
216 downloadsMar 6, 2025
167 downloadsMar 7, 2025
111 downloadsMar 8, 2025
120 downloadsMar 9, 2025
202 downloadsMar 10, 2025
251 downloadsMar 11, 2025
224 downloadsMar 12, 2025
242 downloadsMar 13, 2025
237 downloadsMar 14, 2025
133 downloadsMar 15, 2025
121 downloadsMar 16, 2025
165 downloadsMar 17, 2025
217 downloadsMar 18, 2025
211 downloadsMar 19, 2025
173 downloadsMar 20, 2025
161 downloadsMar 21, 2025
115 downloadsMar 22, 2025
103 downloadsMar 23, 2025
182 downloadsMar 24, 2025
185 downloadsMar 25, 2025
204 downloadsMar 26, 2025
149 downloadsMar 27, 2025
186 downloadsMar 28, 2025
123 downloadsMar 29, 2025
102 downloadsMar 30, 2025
159 downloadsMar 31, 2025
155 downloadsApr 1, 2025
161 downloadsApr 2, 2025
0 downloadsApr 3, 2025
0 downloadsApr 4, 2025
0 downloadsApr 5, 2025
102
292

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 45,080 times in the last 365 days. That's enough downloads to make it mildly famous in niche technical communities. A badge of honor! The day with the most downloads was Mar 05, 2025 with 292 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Data provided by CRAN


Binaries


Dependencies

  • Imports5 packages
  • Suggests8 packages
  • Reverse Depends3 packages
  • Reverse Imports4 packages
  • Reverse Suggests4 packages