4.4 Article

Linear regression with compositional explanatory variables

Journal

JOURNAL OF APPLIED STATISTICS
Volume 39, Issue 5, Pages 1115-1128

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/02664763.2011.644268

Keywords

mixtures; Aitchison geometry on the simplex; isometric logratio transformation; orthonormal coordinates

Funding

  1. Council of the Czech Government MSM [6198959214]
  2. Austrian Science Fund (FWF) [V 142] Funding Source: researchfish

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Compositional explanatory variables should not be directly used in a linear regression model because any inference statistic can become misleading. While various approaches for this problem were proposed, here an approach based on the isometric logratio (ilr) transformation is used. It turns out that the resulting model is easy to handle, and that parameter estimation can be done in like in usual linear regression. Moreover, it is possible to use the ilr variables for inference statistics in order to obtain an appropriate interpretation of the model.

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