Empirical modeling of compositions in chemical engineering

Abstract

Many of the data used in chemical engineering are com­positional. When mass balance based theoretical models cannot be used, and empirical statistical modeling is ap­plied, the compositional, dependent, multivariate nature of the data must be considered. Log-ratios are a powerful approach for transforming compositional data to an uncon­strained vector space of linearly independent coordinates, allowing the application of standard statistical methods. Three of them, the additive, centered, and isometric log-ratios, as well as amalgamations, are introduced in this work, to the chemical engineering community, discussing their potentials, advantages, and possible pitfalls when using them.