Fundamentals of convex optimization for compositional data

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...

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Bibliographic Details
Authors: Saperas Riera, Jordi, Martín Fernández, Josep Antoni, Mateu Figueras, Glòria
Format: article
Publication Date:2023
Country:España
Institution:Universitat Politècnica de Catalunya (UPC)
Repository:UPCommons. Portal del coneixement obert de la UPC
Language:English
OAI Identifier:oai:upcommons.upc.edu:2117/421365
Online Access:https://hdl.handle.net/2117/421365
https://dx.doi.org/10.57645/20.8080.02.11
Access Level:Open access
Keyword:Mathematical statistics
compositional data
logratio
simplex
proportion
function
convexity
optimisation
Estadística matemàtica
Classificació AMS::62 Statistics
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
Description
Summary: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.