Pakiet: r-cran-brglm2 (0.9+dfsg-1)

[ Pakiet źródłowy: r-cran-brglm2  ]

GNU R bias reduction in generalized linear models

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).

Inne pakiety związane z r-cran-brglm2

• dep: r-api-4.0

  pakiet wirtualny udostępniany przez r-base-core

• dep: r-base-core (>= 4.2.2.20221110-2)

  GNU R core of statistical computation and graphics system

• dep: r-cran-enrichwith

  GNU R methods to enrich R Objects with extra components

• dep: r-cran-mass

  GNU R package of Venables and Ripley's MASS

• dep: r-cran-matrix

  GNU R package of classes for dense and sparse matrices

• dep: r-cran-nnet

  GNU R package for feed-forward neural networks

• dep: r-cran-numderiv

  GNU R package for accurate numerical derivatives

• sug: r-cran-covr

  test coverage for GNU R packages

• sug: r-cran-knitr

  GNU R package for dynamic report generation using Literate Programming

• sug: r-cran-rmarkdown

  convert R markdown documents into a variety of formats

• sug: r-cran-tinytest

  Lightweight and Feature Complete Unit Testing Framework

Pobieranie r-cran-brglm2

Pobierz dla wszystkich dostępnych architektur

Architektura	Rozmiar pakietu	Rozmiar po instalacji	Pliki
ppc64el	330,1 KiB	627,0 KiB	[lista plików]