Fundamentals of convex optimization for compositional data
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How to Cite

Saperas Riera, Jordi et al. “Fundamentals of convex optimization for compositional data”. SORT-Statistics and Operations Research Transactions, pp. 323-44, doi:10.57645/20.8080.02.11.


Abstract

Many of the most popular statistical techniques incorporate optimisation problems in their inner workings. A convex optimisation problem is defined as the problem of minimising a convex function over a convex set. When traditional methods are applied to compositional data, misleading and incoherent results could be obtained. In this paper, we fill a gap in the specialised literature by introducing and rigorously defining novel concepts of convex optimisation for compositional data according to the Aitchison geometry. Convex sets and convex functions on the simplex are defined and illustrated.

Keywords

  • compositional data
  • logratio
  • simplex
  • proportion
  • function
  • convexity
  • optimisation
https://doi.org/10.57645/20.8080.02.11
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