Revistes Publicacions URV: SORT - Statistics and Operations Research Transactions> 2018

Evaluating the complexity of some families of functional data

  • Datos identificativos

    Identificador: RP:2471
    Handle: https://hdl.handle.net/20.500.11797/RP2471
    Autores:
    Vieu, PhilippeGoia, AldoBongiorno, Enea
    Resumen:
    In this paper we study the complexity of a functional data set drawn from particular processes by means of a two-step approach. The first step considers a new graphical tool for assessing to which family the data belong: the main aim is to detect whether a sample comes from a monomial or an exponential family. This first tool is based on a nonparametric kNN estimation of small ball probability. Once the family is specified, the second step consists in evaluating the extent of complexity by estimating some specific indexes related to the assigned family. It turns out that the developed methodology is fully free from assumptions on model, distribution as well as dominating measure. Computational issues are carried out by means of simulations and finally the method is applied to analyse some financial real curves dataset.

  • Otros:

    Autor/es de la URV: Vieu, Philippe Goia, Aldo Bongiorno, Enea
    Palabras clave: Small ball probability, log-Volugram, random processes, complexity class, complexity index, knn estimation, functional data analysis
    Resumen: In this paper we study the complexity of a functional data set drawn from particular processes by means of a two-step approach. The first step considers a new graphical tool for assessing to which family the data belong: the main aim is to detect whether a sample comes from a monomial or an exponential family. This first tool is based on a nonparametric kNN estimation of small ball probability. Once the family is specified, the second step consists in evaluating the extent of complexity by estimating some specific indexes related to the assigned family. It turns out that the developed methodology is fully free from assumptions on model, distribution as well as dominating measure. Computational issues are carried out by means of simulations and finally the method is applied to analyse some financial real curves dataset.
    Año de publicación de la revista: 2018
    Tipo de publicación: info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article

  • Palabras clave:

    Small ball probability, log-Volugram, random processes, complexity class, complexity index, knn estimation, functional data analysis

  • Documentos:

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