Classification of probability density functions in the framework of Bayes spaces: methods and applications

• Ivana Pavlů ^[2] ; Alessandra Menafoglio ^[1] ; Enea Bongiorno ^[3] ; Karel Hron ^[2]
  1. [1] Polytechnic University of Milan

     Polytechnic University of Milan

     Milán, Italia

     
  2. [2] Palacky University Olomouc
  3. [3] Universita degli Studi del Piemonte Orientale, Novara

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• Localización: Sort: Statistics and Operations Research Transactions, ISSN 1696-2281, Vol. 47, Nº. 2, 2023, págs. 41-50
• Idioma: inglés
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• Resumen

  • The process of supervised classifcation when the data set consists of probability density functions is studied. Due to the relative information contained in densities, it is ne- cessary to convert the functional data analysis methods into an appropriate framework, here represented by the Bayes spaces. This work develops Bayes space counterparts to a set of commonly used functional methods with a focus on classifcation. Hereby, a clear guideline is provided on how some classifcation approaches can be adapted for the case of densities. Comparison of the methods is based on simulation studies and real-world applications, refecting their respective strengths and weaknesses