Changes in Version 3.1-4

  o In betatree() the "xlevels" attribute from partykit::mob is now correctly
    stored in $levels (rather than $xlevels) of the returned object.


Changes in Version 3.1-3

  o Added "IGNORE_RDIFF" flags in some examples in order to avoid showing
    diffs due to small numeric deviations in some checks (especially on CRAN).


Changes in Version 3.1-2

  o 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.


Changes in Version 3.1-1

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


Changes in Version 3.1-0

  o 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".

  o Included "grDevices" in Imports.
  
  o Fixed model.frame() method for "betareg" objects which do not store the
    model frame in $model.

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


Changes in Version 3.0-5

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

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


Changes in Version 3.0-4

  o For some datasets betareg() would just "hang" because dbeta() "hangs"
    for certain extreme parameter combinations (in current R versions).
    betareg() now tries to catches these cases in order to avoid the problem.
    
  o 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.


Changes in Version 3.0-3

  o The predict() method gained support for type = "quantile", so that
    quantiles of the response distribution can be predicted.

  o 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.


Changes in Version 3.0-2

  o Avoid .Call()ing logit link functions directly, instead
    use elements of make.link("logit").


Changes in Version 3.0-1

  o Small consistency updates in labeling coefficients for
    current R-devel.


Changes in Version 3.0-0

  o 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.


Changes in Version 2.4-1

  o Formula interface for betamix() changed to allow for three parts
    in the right hand side where the third part relates to the
    concomitant variables.

  o 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.


Changes in Version 2.4-0

  o 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.
    
  o 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).

  o Enabled fitting of beta regression models without coefficients in the
    mean equation.

  o 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).

  o 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.

  o 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.


Changes in Version 2.3-0

  o 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.

  o 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.

  o Added tests/vignette-betareg.R based on the models fitted
    in vignette("betareg", package = "betareg").


Changes in Version 2.2-3

  o The "levels" element of a "betareg" object is now a list
    with components "mean", "precision", and "full" to match
    the "terms" of the object.
    
  o Improved data handling bug in predict() method.


Changes in Version 2.2-2

  o Documentation updates for ?gleverage.
  

Changes in Version 2.2-1

  o Package now published in Journal of Statistical Software,
    see http://www.jstatsoft.org/v34/i02/
    and citation("betareg") within R.

  o Bug fix and improvements in gleverage() method for "betareg"
    objects: Analytic second derivatives are now used and
    variable dispersion models are handled correctly.


Changes in Version 2.2-0

  o dbeta(..., log = TRUE) is now used for computing the
    log-likelihood which is numerically more stable
    than the previous hand-crafted version.
    
  o 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.
    
  o Various documentation improvements, especially in the
    vignette.


Changes in Version 2.1-2

  o 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.

  o 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.    

  o Allowed all link functions (in mean model) that are
    available in make.link() for binary responses, and added
    log-log link.

  o 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").

  o Default in residuals() (as well as in the related plot()
    and summary() components) is now to use standardized
    weighted residuals 2 (type = "sweighted2").


Changes in Version 2.0-0

  o 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.
    
  o betareg(): more standard formula-interface arguments;
    "betareg" objects do _not_ inherit from "lm" anymore.
  
  o betareg.fit(): renamed from br.fit(), enhanced interface
    with more arguments and returned information. Untested
    support of weighted regressions is enabled.
    
  o betareg.control(): new function encapsulating control
    of optim(), slightly modified default values.

  o anova() method was removed, use lrtest() from "lmtest"
    package instead.
    
  o gen.lev.betareg() was changed to gleverage() method
    (with new generic) and a bug in the method was fixed.
    
  o envelope.beta() was removed and is now included in
    plot() method for "betareg" objects.
    
  o Datasets "prater" and "pratergrouped" were incorporated
    into a single "GasolineYield" dataset.

  o New data set "FoodExpenditure" from Griffiths et al. (1993),
    replicating second application from Ferrari and Cribari-Neto
    (2004).
  
  o Added NAMESPACE.

  o 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.
