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Log-ratio methods in mixture models for compositional data sets

Research output: Contribution to journalScientific articlepeer-review

11 Citations (Scopus)

Abstract

When traditional methods are applied to compositional data misleading and incoherent results could be obtained. Finite mixtures of multivariate distributions are becoming increasingly important nowadays. In this paper, traditional strategies to fit a mixture model into compositional data sets are revisited and the major difficulties are detailed. A new proposal using a mixture of distributions defined on orthonormal log-ratio coordinates is introduced. A real data set analysis is presented to illustrate and compare the different methodologies.

Original languageEnglish
Pages (from-to)349-374
Number of pages26
JournalSORT
Volume40
Issue number2
Publication statusPublished - 1 Jul 2016

Keywords

  • Compositional data
  • Finite mixture
  • Log ratio
  • Model-based clustering
  • Normal distribution
  • Orthonormal coordinates
  • Simplex

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