Modeling asymmetric compositional data

Resumen

Compositional data belong to the simplex sample space, but they are transformed to the sample space of the real numbers using the additive log-ratio transformation to allow the application of standard statistical techniques. This study aims to model compositional skewed data of three soil components after additive log-ratio transformation. The current modeling was done for compositional data of sand, silt and clay (simplex), and bivariate data (real) using the standard skew theory with and without the inclusion of the covariate soil porosity. The analyses were run using the R statistical software and the package sn, and the goodness-of-fit was found after applying the covariate.