Articles producció científicaGestió d'Empreses

A Fuzzy-Random Extension of the Lee-Carter Mortality Prediction Model

  • Datos identificativos

    Identificador:  imarina:5874626
    Autores:  de Andres-Sanchez, Jorge; Gonzalez-Vila Puchades, Laura
    Resumen:
    The Lee-Carter model is a useful dynamic stochastic model to represent the evolution of central mortality rates throughout time. This model only considers the uncertainty about the coefficient related to the mortality trend over time but not to the age-dependent coefficients. This paper proposes a fuzzy-random extension of the Lee-Carter model that allows quantifying the uncertainty of both kinds of parameters. As it is commonplace in actuarial literature, the variability of the time-dependent index is modeled as an ARIMA time series. Likewise, the uncertainty of the age-dependent coefficients is also quantified, but by using triangular fuzzy numbers. The consideration of this last hypothesis requires developing and solving a fuzzy regression model. Once the fuzzy-random extension has been introduced, it is also shown how to obtain some variables linked with central mortality rates such as death probabilities or life expectancies by using fuzzy numbers arithmetic. It is simultaneously shown the applicability of our developments with data of Spanish male population in the period 1970-2012. Finally we make a comparative assessment of our method with alternative Lee-Carter model estimates on 16 Western Europe populations. (c) 2019 The Authors. Published by Atlantis Press SARL.
  • Otros:

    Enlace a la fuente original: https://www.atlantis-press.com/journals/ijcis/125913525
    Referencia de l'ítem segons les normes APA: de Andres-Sanchez, Jorge; Gonzalez-Vila Puchades, Laura; (2019). A Fuzzy-Random Extension of the Lee-Carter Mortality Prediction Model. International Journal Of Computational Intelligence Systems, 12(2), 775-794. DOI: 10.2991/ijcis.d.190626.001
    Referencia al articulo segun fuente origial: International Journal Of Computational Intelligence Systems. 12 (2): 775-794
    DOI del artículo: 10.2991/ijcis.d.190626.001
    Año de publicación de la revista: 2019
    Entidad: Universitat Rovira i Virgili
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Fecha de alta del registro: 2025-02-19
    Autor/es de la URV: De Andrés Sánchez, Jorge
    Departamento: Gestió d'Empreses
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Tipo de publicación: Journal Publications
    ISSN: 18756883
    Autor según el artículo: de Andres-Sanchez, Jorge; Gonzalez-Vila Puchades, Laura;
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Áreas temáticas: Interdisciplinar, General computer science, Engenharias iv, Computer science, interdisciplinary applications, Computer science, artificial intelligence, Computer science (miscellaneous), Computer science (all), Computational mathematics, Ciência da computação
    Direcció de correo del autor: jorge.deandres@urv.cat, jorge.deandres@urv.cat
  • Palabras clave:

    Lee–carter model
    Lee-carter model
    Fuzzy-random modelling
    Fuzzy-random modeling
    Fuzzy regression
    Fuzzy numbers
    Computational Mathematics
    Computer Science (Miscellaneous)
    Computer Science
    Artificial Intelligence
    Interdisciplinary Applications
    Interdisciplinar
    General computer science
    Engenharias iv
    Computer science (all)
    Ciência da computação
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