  This paper proposes a general class of regression models for continuous
proportions when the data contain zeros or ones. The proposed class of models
assumes that the response variable has a mixed continuous-discrete distribution
with probability mass at zero or one. The beta distribution is used to describe
the continuous component of the model, since its density has a wide range of
different shapes depending on the values of the two parameters that index the
distribution. We use a suitable parameterization of the beta law in terms of
its mean and a precision parameter. The parameters of the mixture distribution
are modeled as functions of regression parameters. We provide inference,
diagnostic, and model selection tools for this class of models. A practical
application that employs real data is presented.
