betareg 3.2-2
- Added family functions for generalized additive models for location, scale, and shape (GAMLSS) with package bamlss or gamlss2 using frequentist and Bayesian estimation, respectively. Standard beta regression using the parameterization with
mu
andphi
is provided bybetar_family()
andxbetax_family()
provides the new extended-support beta mixture (XBX) regression.
betareg 3.2-1
New working paper “Extended-Support Beta Regression for [0, 1] Responses” by Ioannis Kosmidis and Achim Zeileis in the arXiv.org E-Print Archive, doi:10.48550/arXiv.2409.07233.
New package web page (via
altdoc
/quarto
) at https://topmodels.R-Forge.R-project.org/betareg/Extended functionality of
predict()
method forbetareg
objects and enhanced the corresponding documentation, see?predict.betareg
.Turned
vignette("betareg", package = "betareg")
andvignette("betareg-ext", package = "betareg")
from Sweave into Quarto vignettes. Some improvements/updates in the text.
betareg 3.2-0
Major extension in
betareg()
: In addition to classic beta regression for responses in the open interval (0, 1), extended-support beta regression is added which can model responses in the closed interval [0, 1] (i.e., including boundary observations at 0 and/or 1). This is accomplished by adding two new response distributions: The extended-support beta distribution ("xbeta"
) leverages an underlying symmetric four-parameter beta distribution with exceedence parameternu
to obtain support [-nu, 1 + nu] that is subsequently censored to [0, 1] in order to obtain point masses at the boundary values 0 and 1. The extended-support beta mixture distribution ("xbetax"
) is a continuous mixture of extended-support beta distributions where the exceedence parameter follows an exponential distribution with meannu
(rather than a fixed value ofnu
). The latter"xbetax"
specification is used by default in case of boundary observations at 0 and/or 1. The"xbeta"
specification with fixednu
is mostly for testing and debugging purposes.Quantile residuals are added to the
residuals()
method forbetareg
objects. They are easy to compute and have good distributional properties. Hence, they are the new default residuals.Bug fix in
pseudo.r.squared
computation for weighted models where previously the weights were erroneously ignored (reported by Ray Tayek).Bug fixes in
betatree()
: Split points were computed incorrectly due to wrong sign of the log-likelihood (reported by Se-Wan Jeong). And trees with only intercepts for bothmu
andphi
could not be fitted (reported by Ludwig Hothorn).
betareg 3.1-4
- In
betatree()
the"xlevels"
attribute frompartykit::mob
is now correctly stored in$levels
(rather than$xlevels
) of the returned object.
betareg 3.1-3
- Added
IGNORE_RDIFF
flags in some examples in order to avoid showing diffs due to small numeric deviations in some checks (especially on CRAN).
betareg 3.1-2
- Added
suppressWarnings(RNGversion("3.5.0"))
in those places whereset.seed()
was used to assure exactly reproducible results from R 3.6.0 onwards.
betareg 3.1-1
- Conditional registration of
sctest()
method forbetatree
objects whenstrucchange
package is loaded.
betareg 3.1-0
The
betatree()
function now uses the newmob()
implementation from thepartykit
package (instead of the oldparty
package). The user interface essentially remained the same but now many more options are available through the newmob()
function. The returned model object is now inheriting frommodelparty
/party
.Included
grDevices
in Imports.Fixed
model.frame()
method forbetareg
objects which do not store the model frame in$model
.betamix()
gained argumentsweights
(case weights for observations) andoffset
(for the mean linear predictor).
betareg 3.0-5
The
Formula
package is now only in Imports but not Depends (see below).Method
FLXgetModelmatrix
forFLXMRbeta
objects modified due to changes inflexmix
2.3.12.
betareg 3.0-4
For some datasets
betareg()
would just “hang” becausedbeta()
“hangs” for certain extreme parameter combinations (in current R versions).betareg()
now tries to catch these cases in order to avoid the problem.Depends/Imports/Suggests have been rearranged to conform with current CRAN check policies. This is the last version of
betareg
to have theFormula
package in Depends - from the next version onwards it will only be in Imports.
betareg 3.0-3
The
predict()
method gained support fortype = "quantile"
, so that quantiles of the response distribution can be predicted.The
Formula
package is now not only in the list of dependencies but is also imported in theNAMESPACE
, in order to facilitate importingbetareg
in other packages.
betareg 3.0-2
- Avoid
.Call()
-ing logit link functions directly, instead use elements ofmake.link("logit")
.
betareg 3.0-1
- Small consistency updates in labeling coefficients for current R-devel.
betareg 3.0-0
- New release accompanying the second JSS paper: “Extended Beta Regression in R: Shaken, Stirred, Mixed, and Partitioned” by Gruen, Kosmidis, and Zeileis which appears as Journal of Statistical Software 48(11). See also
citation("betareg")
. The paper presents the recently introduced features: bias correction/reduction inbetareg()
, recursive partitioning viabetatree()
, and finite mixture modeling viabetamix()
. See alsovignette("betareg-ext", package = "betareg")
for the vignette version within the package.
betareg 2.4-1
Formula interface for
betamix()
changed to allow for three parts in the right hand side where the third part relates to the concomitant variables.Modified the internal structure of vignettes/tests. The original vignettes are now moved to the vignettes directory, containing also .Rout.save files. Similarly, an .Rout.save for the examples is added in the tests directory.
betareg 2.4-0
Support bias-corrected (BC) and bias-reduced (BR) maximum likelihood estimation of beta regressions. See the
type
argument ofbetareg()
. To enable BC/BR, an additional Fisher scoring iteration was added that (by default) also enhances the usual ML results.New
vignette("betareg-ext", package = "betareg")
introducing BC/BR estimation along with the recent additions beta regression trees and latent class beta regression (aka finite mixture beta regression models).Enabled fitting of beta regression models without coefficients in the mean equation.
Enabled usage of offsets in both parts of the model, i.e., one can use
betareg(y ~ x + offset(o1) | z + offset(o2))
which is also equivalent tobetareg(y ~ x | z + offset(o2), offset = o1)
, i.e., theoffset
argument of betareg is employed for the mean equation only. Consequently,betareg_object$offset
is now a list with two elements (mean
/precision
).Added warning and ad-hoc workaround in the starting value selection of
betareg.fit()
for the precision model. If no valid starting value can be obtained, a warning is issued andc(1, 0, ..., 0)
is employed.Added
betareg_object$nobs
in the return object containing the number of observations with non-zero weights. Thennobs()
can be used to extract this and consequentlyBIC()
can be used to compute the BIC.
betareg 2.3-0
New
betatree()
function for beta regression trees based on model-based recursive partitioning.betatree()
leverages themob()
function from theparty
package. For enabling this plug-in, aStatModel
constructorbetaReg()
is provided based on themodeltools
package.New
betamix()
function for latent class beta regression, or finite mixture beta regression models.betamix()
leverages theflexmix()
function from theflexmix
package. For enabling this plug-in, the driverFLXMRbeta()
is provided.Added tests/vignette-betareg.R based on the models fitted in
vignette("betareg", package = "betareg")
.
betareg 2.2-3
The
"levels"
element of abetareg
object is now a list with components"mean"
,"precision"
, and"full"
to match the"terms"
of the object.Improved data handling bug in
predict()
method.
betareg 2.2-2
- Documentation updates for
?gleverage
.
betareg 2.2-1
Package now published in Journal of Statistical Software, see https://www.jstatsoft.org/v34/i02/ and
citation("betareg")
within R.Bug fix and improvements in
gleverage()
method forbetareg
objects: Analytic second derivatives are now used and variable dispersion models are handled correctly.
betareg 2.2-0
dbeta(..., log = TRUE)
is now used for computing the log-likelihood which is numerically more stable than the previous hand-crafted version.The starting values in the dispersion regression are now chosen differently, resulting in a somewhat more robust specification of starting values. The intercept is computed as described in Ferrari & Cribari-Neto (2004), plus a link transformation (if any). All further parameters (if any) are initially set to zero. See also the vignette for details.
Various documentation improvements, especially in the vignette.
betareg 2.1-2
New vignette (written by Francisco Cribari-Neto and Z)
introducing the package and replicating a range of publications related to beta regression:vignette("betareg", package = "betareg")
provides some theoretical background, a discussion of the implementation and several hands-on examples.Implemented an optional precision model, yielding variable dispersion. The precision parameter
phi
may depend on a linear predictor, as suggested by Simas, Barreto-Souza, and Rocha (2010). In single part formulas of typey ~ x1 + x2
,phi
is by default assumed to be constant, i.e., an intercept plus identity link. But it can be extended toy ~ x1 + x2 | z1 + z2
wherephi
depends onz1 + z2
, by default through a log link.Allowed all link functions (in mean model) that are available in
make.link()
for binary responses, and added log-log link.Added data and replication code for Smithson & Verkuilen (2006, Psychological Methods). See
?ReadingSkills
,?MockJurors
,?StressAnxiety
as well as the complete replication code indemo("SmithsonVerkuilen2006")
.Default in
residuals()
(as well as in the relatedplot()
andsummary()
components) is now to use standardized weighted residuals 2 (type = "sweighted2"
).
betareg 2.0-0
Package
betareg
was orphaned on CRAN, Z took over as maintainer, ended up re-writing the whole package. The package still provides all functionality as before but the interface is not fully backward-compatible.betareg()
: More standard formula-interface arguments;betareg
objects do not inherit fromlm
anymore.betareg.fit()
: Renamed frombr.fit()
, enhanced interface with more arguments and returned information. Untested support of weighted regressions is enabled.betareg.control()
: New function encapsulating control ofoptim()
, slightly modified default values.anova()
method was removed, uselrtest()
fromlmtest
package instead.gen.lev.betareg()
was changed togleverage()
method (with new generic) and a bug in the method was fixed.envelope.beta()
was removed and is now included inplot()
method forbetareg
objects.Datasets
prater
andpratergrouped
were incorporated into a singleGasolineYield
dataset.New data set
FoodExpenditure
from Griffiths et al. (1993), replicating second application from Ferrari and Cribari-Neto (2004).Added
NAMESPACE
.The
residuals()
method now has three further types of residuals suggested by Espinheira et al. (2008) who recommend to use “standardized weighted residuals 2” (type = "sweighted2"
). The default are Pearson (aka standardized) residuals.