mlsanityData to 14 Oct 2026

A Dirichlet Regression Model for Compositional Data with Zeros

arXiv 1410.5011 ↗First posted 18 Oct 2014stat.MEcited by 1

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Abstract (arXiv)

Compositional data are met in many different fields, such as economics, archaeometry, ecology, geology and political sciences. Regression where the dependent variable is a composition is usually carried out via a log-ratio transformation of the composition or via the Dirichlet distribution. However, when there are zero values in the data these two ways are not readily applicable. Suggestions for this problem exist, but most of them rely on substituting the zero values. In this paper we adjust the Dirichlet distribution when covariates are present, in order to allow for zero values to be present in the data, without modifying any values. To do so, we modify the log-likelihood of the Dirichlet distribution to account for zero values. Examples and simulation studies exhibit the performance of the zero adjusted Dirichlet regression.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 18 Oct 2014.

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