c(person(given = "Achim", family = "Zeileis", role =
c("aut", "cre"), email = "Achim.Zeileis@R-project.org"),
person(given = "Francisco", family = "Cribari-Neto", role =
"aut", email = "cribari@ufpe.br"), person(given = "Bettina",
family = "Gruen", role = "aut", email =
"Bettina.Gruen@jku.at"), person(given = "Ioannis", family =
"Kosmidis", role = "aut", email = "ioannis@stats.ucl.ac.uk"),
person(given = c("Alexandre", "B."), family = "Simas", role =
"ctb", comment = "earlier version by"), person(given =
c("Andrea", "V."), family = "Rocha", role = "ctb", comment =
"earlier version by"))
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)
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.

graphics, methods, flexmix, lmtest, modeltools, sandwich

graphics, methods, flexmix, Formula, lmtest, modeltools,
sandwich

c(person(given = "Achim", family = "Zeileis", role = c("aut", "cre"), email = "Achim.Zeileis@R-project.org"),
person(given = "Francisco", family = "Cribari-Neto", role = "aut", email = "cribari@ufpe.br"),
person(given = "Bettina", family = "Gruen", role = "aut", email = "Bettina.Gruen@jku.at"),
person(given = "Ioannis", family = "Kosmidis", role = "aut", email = "ioannis@stats.ucl.ac.uk"),
person(given = c("Alexandre", "B."), family = "Simas", role = "ctb", comment = "earlier version by"),
person(given = c("Andrea", "V."), family = "Rocha", role = "ctb", comment = "earlier version by"))
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.
graphics, methods, stats, flexmix, lmtest, modeltools,
sandwich
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)