2021/08/30 by Claudia Wehrhahn, Wehrhahn, Claudia, Andrés F. Barrientos +3
Computer Science · Decision Sciences · Engineering · #FOS: Computer and information sciences #Geochemistry and Geologic Mapping #Grey System Theory Applications #Methodology (stat.ME) #Mineral Processing and Grinding
paper · pdf · doi:10.48550/arxiv.2108.13403
openalex publication_date 2021/08/30 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
We discuss Bayesian nonparametric procedures for the regression analysis of compositional responses, that is, data supported on a multivariate simplex. The procedures are based on a modified class of multivariate Bernstein polynomials and on the use of dependent stick-breaking processes. A general model and two simplified versions of the general model are discussed. Appealing theoretical properties such as continuity, association structure, support, and consistency of the posterior distribution are established. Additionally, we exploit the use of spike-and-slab priors for choosing the version of the model that best adapts to the complexity of the underlying true data-generating distribution. The performance of the proposed model is illustrated in a simulation study and in an application to solid waste data from Colombia.