NEWS.md

In betareg: Beta 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 for betareg objects and enhanced the corresponding documentation, see ?predict.betareg.

• Turned vignette("betareg", package = "betareg") and vignette("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 parameter nu 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 mean nu (rather than a fixed value of nu). The latter "xbetax" specification is used by default in case of boundary observations at 0 and/or 1. The "xbeta" specification with fixed nu is mostly for testing and debugging purposes.

• Quantile residuals are added to the residuals() method for betareg 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 both mu and phi could not be fitted (reported by Ludwig Hothorn).

betareg 3.1-4

• In betatree() the "xlevels" attribute from partykit::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 where set.seed() was used to assure exactly reproducible results from R 3.6.0 onwards.

betareg 3.1-1

• Conditional registration of sctest() method for betatree objects when strucchange package is loaded.

betareg 3.1-0

• The betatree() function now uses the new mob() implementation from the partykit package (instead of the old party package). The user interface essentially remained the same but now many more options are available through the new mob() function. The returned model object is now inheriting from modelparty/party.

• Included grDevices in Imports.

• Fixed model.frame() method for betareg objects which do not store the model frame in $model.

• betamix() gained arguments weights (case weights for observations) and offset (for the mean linear predictor).

betareg 3.0-5

• The Formula package is now only in Imports but not Depends (see below).

• Method FLXgetModelmatrix for FLXMRbeta objects modified due to changes in flexmix 2.3.12.

betareg 3.0-4

• For some datasets betareg() would just "hang" because dbeta() "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 the Formula package in Depends - from the next version onwards it will only be in Imports.

betareg 3.0-3

• The predict() method gained support for type = "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 the NAMESPACE, in order to facilitate importing betareg in other packages.

betareg 3.0-2

• Avoid .Call()-ing logit link functions directly, instead use elements of make.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 in betareg(), recursive partitioning via betatree(), and finite mixture modeling via betamix(). See also vignette("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 of betareg(). 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 to betareg(y ~ x | z + offset(o2), offset = o1), i.e., the offset 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 and c(1, 0, ..., 0) is employed.

• Added betareg_object$nobs in the return object containing the number of observations with non-zero weights. Then nobs() can be used to extract this and consequently BIC() 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 the mob() function from the party package. For enabling this plug-in, a StatModel constructor betaReg() is provided based on the modeltools package.

• New betamix() function for latent class beta regression, or finite mixture beta regression models. betamix() leverages the flexmix() function from the flexmix package. For enabling this plug-in, the driver FLXMRbeta() 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 a betareg 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 for betareg 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 type y ~ x1 + x2, phi is by default assumed to be constant, i.e., an intercept plus identity link. But it can be extended to y ~ x1 + x2 | z1 + z2 where phi depends on z1 + 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 in demo("SmithsonVerkuilen2006").

• Default in residuals() (as well as in the related plot() and summary() 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 from lm anymore.

• betareg.fit(): Renamed from br.fit(), enhanced interface with more arguments and returned information. Untested support of weighted regressions is enabled.

• betareg.control(): New function encapsulating control of optim(), slightly modified default values.

• anova() method was removed, use lrtest() from lmtest package instead.

• gen.lev.betareg() was changed to gleverage() method (with new generic) and a bug in the method was fixed.

• envelope.beta() was removed and is now included in plot() method for betareg objects.

• Datasets prater and pratergrouped were incorporated into a single GasolineYield 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.

betareg documentation built on Sept. 13, 2024, 1:07 a.m.