betareg: Beta Regression

Beta regression for modeling beta-distributed dependent variables, e.g., rates and proportions. In addition to maximum likelihood regression (for both mean and precision of a beta-distributed response), bias-corrected and bias-reduced estimation as well as finite mixture models and recursive partitioning for beta regressions are provided.

Version: 3.1-3
Depends: R (≥ 3.0.0)
Imports: graphics, grDevices, methods, stats, flexmix, Formula, lmtest, modeltools, sandwich
Suggests: car, lattice, partykit, strucchange
Published: 2020-02-03
Author: Achim Zeileis [aut, cre], Francisco Cribari-Neto [aut], Bettina Gruen [aut], Ioannis Kosmidis [aut], Alexandre B. Simas [ctb] (earlier version by), Andrea V. Rocha [ctb] (earlier version by)
Maintainer: Achim Zeileis <Achim.Zeileis at R-project.org>
License: GPL-2 | GPL-3
NeedsCompilation: no
Citation: betareg citation info
Materials: NEWS
In views: Econometrics, Psychometrics, SocialSciences
CRAN checks: betareg results

Downloads:

Reference manual: betareg.pdf
Vignettes: Extended Beta Regression in R: Shaken, Stirred, Mixed, and Partitioned
Beta Regression in R
Package source: betareg_3.1-3.tar.gz
Windows binaries: r-devel: betareg_3.1-3.zip, r-release: betareg_3.1-3.zip, r-oldrel: betareg_3.1-3.zip
macOS binaries: r-release: betareg_3.1-3.tgz, r-oldrel: betareg_3.1-3.tgz
Old sources: betareg archive

Reverse dependencies:

Reverse depends: biasbetareg, mfx
Reverse imports: bbreg, BetaPASS, BiSeq, distreg.vis, DMRcaller, earlygating, gcmr, hier.part, MarginalMediation, opticut, PASSED, plsRbeta, SetMethods, vortexR
Reverse suggests: agridat, AICcmodavg, betaboost, broom, DeclareDesign, dominanceanalysis, effects, ggeffects, insight, mi, parameters, performance, rstanarm
Reverse enhances: enrichwith, margins, MuMIn, prediction, stargazer

Linking:

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