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: | 3.1-1 |
Depends: | R (≥ 3.0.0) |
Imports: | graphics, grDevices, methods, stats, flexmix, Formula, lmtest, modeltools, sandwich |
Suggests: | car, lattice, partykit, strucchange |
Published: | 2018-09-28 |
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 |
Reference manual: | betareg.pdf |
Vignettes: |
Extended Beta Regression in R: Shaken, Stirred, Mixed, and Partitioned Beta Regression in R |
Package source: | betareg_3.1-1.tar.gz |
Windows binaries: | r-devel: betareg_3.1-1.zip, r-release: betareg_3.1-1.zip, r-oldrel: betareg_3.1-1.zip |
OS X binaries: | r-release: betareg_3.1-1.tgz, r-oldrel: betareg_3.1-1.tgz |
Old sources: | betareg archive |
Reverse depends: | biasbetareg, mfx, SetMethods |
Reverse imports: | earlygating, gcmr, MarginalMediation, opticut, plsRbeta, vortexR |
Reverse suggests: | agridat, AICcmodavg, betaboost, broom, DeclareDesign, effects, insight, mi, rstanarm |
Reverse enhances: | margins, MuMIn, prediction, stargazer, texreg |
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