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.
