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Beta Regression in R

Cribari-Neto, Francisco and Zeileis, Achim (2009) Beta Regression in R. Research Report Series / Department of Statistics and Mathematics, 98. Department of Statistics and Mathematics x, WU Vienna University of Economics and Business, Vienna.

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Abstract

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.

Item Type: Paper
Keywords: beta regression / rates / proportions / R
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Depositing User: Repository Administrator
Date Deposited: 15 Dec 2009 00:10
Last Modified: 27 Feb 2017 16:09
URI: http://epub.wu.ac.at/id/eprint/726

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