A folded model for compositional data analysis. (23rd July 2020)

• Record Type: Journal Article
• Authors: Tsagris, Michail; Stewart, Connie
• Is Part Of: Australian & New Zealand journal of statistics. Volume 62:Number 2(2020)
• Page Start: 249
• Page End: 277
• Publication Date: 2020-07-23
• Subjects: α‐transformation -- EM‐algorithm -- compositional data -- folding transformation; Statistics -- Periodicals; 519.5
• DOI: 10.1111/anzs.12289
• Languages: English
• ISSNs: 1369-1473

Abstract

Summary: A folded type model is developed for analysing compositional data. The proposed model involves an extension of the α ‐transformation for compositional data and provides a new and flexible class of distributions for modelling data defined on the simplex sample space. Despite its rather seemingly complex structure, employment of the EM algorithm guarantees efficient parameter estimation. The model is validated through simulation studies and examples which illustrate that the proposed model performs better in terms of capturing the data structure, when compared to the popular logistic normal distribution, and can be advantageous over a similar model without folding. Abstract : A new flexible model for compositional data that involves the α‐transformation.