Estimation and inference from generalized linear models based on various methods for bias reduction. 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. (2016) <arXiv:1604.04768>, 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) <http://www.jstor.org/stable/2345592>. 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 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). 'brglm2' also provides pre-fit and post-fit methods for detecting separation and infinite maximum likelihood estimates in binomial response generalized linear models.

Version: | 0.5.1 |

Depends: | R (≥ 3.3.0) |

Imports: | MASS, stats, Matrix, graphics, nnet, enrichwith, lpSolveAPI, numDeriv |

Suggests: | testthat, knitr, rmarkdown, covr |

Published: | 2019-02-14 |

Author: | Ioannis Kosmidis [aut, cre], Kjell Konis [ctb], Euloge Clovis Kenne Pagui [ctb], Nicola Sartori [ctb] |

Maintainer: | Ioannis Kosmidis <ioannis.kosmidis at warwick.ac.uk> |

BugReports: | https://github.com/ikosmidis/brglm2/issues |

License: | GPL-3 |

URL: | https://github.com/ikosmidis/brglm2 |

NeedsCompilation: | yes |

Citation: | brglm2 citation info |

Materials: | README NEWS |

CRAN checks: | brglm2 results |

Reference manual: | brglm2.pdf |

Vignettes: |
Adjacent category logit models using brglm2 Bias reduction in generalized linear models Multinomial logistic regression using brglm2 Detecting separation and infinite estimates in binomial response GLMs |

Package source: | brglm2_0.5.1.tar.gz |

Windows binaries: | r-devel: brglm2_0.5.1.zip, r-release: brglm2_0.5.1.zip, r-oldrel: brglm2_0.5.1.zip |

OS X binaries: | r-release: brglm2_0.5.1.tgz, r-oldrel: brglm2_0.5.1.tgz |

Old sources: | brglm2 archive |

Reverse imports: | SOIL |

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