A Dirichlet Regression Model for Compositional Data with Zeros
- 作者: Tsagris M.1, Stewart C.2
-
隶属关系:
- Department of Computer Science
- Department of Mathematics and Statistics
- 期: 卷 39, 编号 3 (2018)
- 页面: 398-412
- 栏目: Article
- URL: https://journals.rcsi.science/1995-0802/article/view/201853
- DOI: https://doi.org/10.1134/S1995080218030198
- ID: 201853
如何引用文章
详细
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.
作者简介
Michail Tsagris
Department of Computer Science
编辑信件的主要联系方式.
Email: mtsagris@yahoo.gr
希腊, Heraklion Crete
Connie Stewart
Department of Mathematics and Statistics
Email: mtsagris@yahoo.gr
加拿大, Saint John, New Brunswick
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