3,082 research outputs found
Beta Regression in R
The class of beta regression models is commonly used by practitioners to model variables that assume values in the standard unit interval (0, 1). It is based on the assumption that the dependent variable is beta-distributed and that its mean is related to a set of regressors through a linear predictor with unknown coefficients and a link function. The model also includes a precision parameter which may be constant or depend on a (potentially different) set of regressors through a link function as well. This approach naturally incorporates features such as heteroskedasticity or skewness which are commonly observed in data taking values in the standard unit interval, such as rates or proportions. This paper describes the betareg package which provides the class of beta regressions in the R system for statistical computing. The underlying theory is briefly outlined, the implementation discussed and illustrated in various replication exercises.Series: Research Report Series / Department of Statistics and Mathematic
Beta Regression in R
The class of beta regression models is commonly used by practitioners to model variables that assume values in the standard unit interval (0, 1). It is based on the assumption that the dependent variable is beta-distributed and that its mean is related to a set of regressors through a linear predictor with unknown coefficients and a link function. The model also includes a precision parameter which may be constant or depend on a (potentially different) set of regressors through a link function as well. This approach naturally incorporates features such as heteroskedasticity or skewness which are commonly observed in data taking values in the standard unit interval, such as rates or proportions. This paper describes the betareg package which provides the class of beta regressions in the R system for statistical computing. The underlying theory is briefly outlined, the implementation discussed and illustrated in various replication exercises.
A general class of zero-or-one inflated beta regression models
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.Comment: 21 pages, 3 figures, 5 tables. Computational Statistics and Data
Analysis, 17 October 2011, ISSN 0167-9473
(http://www.sciencedirect.com/science/article/pii/S0167947311003628
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