Modelling compositional data with structural zero values

Compositional data are positive multivariate data whose sum equals 1. A popular method to analyze such data is via log–ratio transformations, which are however not applicable when zero values are present. In this paper we present a conditional logistic normal distribution suitable for compositional data with structural zero values. The model is applicable to arbitrary dimensions and the EM algorithm guarantees a fast implementation. The regression setting is also presented and a comparison to the Dirichlet analogue is performed.