Quotation Maier, Marco. 2014. DirichletReg: Dirichlet Regression for Compositional Data in R. Research Report Series / Department of Statistics and Mathematics, 125.


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Abstract

Dirichlet regression models can be used to analyze a set of variables lying in a bounded interval that sum up to a constant (e.g., proportions, rates, compositions, etc.) exhibiting skewness and heteroscedasticity, without having to transform the data. There are two parametrization for the presented model, one using the common Dirichlet distribution's alpha parameters, and a reparametrization of the alpha's to set up a mean-and-dispersion-like model. By applying appropriate link-functions, a GLM-like framework is set up that allows for the analysis of such data in a straightforward and familiar way, because interpretation is similar to multinomial logistic regression. This paper gives a brief theoretical foundation and describes the implementation as well as application (including worked examples) of Dirichlet regression methods implemented in the package DirichletReg (Maier, 2013) in the R language (R Core Team, 2013).

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Working/discussion paper, preprint
Language English
Title DirichletReg: Dirichlet Regression for Compositional Data in R
Title of whole publication Research Report Series / Department of Statistics and Mathematics, 125
Year 2014
URL http://epub.wu.ac.at/4077/

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People
Maier, Marco (Former researcher)
Organization
Institute for Statistics and Mathematics IN (Details)
Research areas (Ă–STAT Classification 'Statistik Austria')
1105 Computer software (Details)
1162 Statistics (Details)
5509 Psychological methodology (Details)
5700 Applied statistics, social statistics (Details)
5701 Applied statistics (Details)
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