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

  • Datos identificativos

    Identificador: imarina:5874626
    Autores:
    de Andres-Sanchez, JorgeGonzalez-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:

    Autor según el artículo: de Andres-Sanchez, Jorge; Gonzalez-Vila Puchades, Laura;
    Departamento: Gestió d'Empreses
    Autor/es de la URV: De Andrés Sànchez, Jorge
    Palabras clave: Lee–carter model Lee-carter model Fuzzy-random modelling Fuzzy-random modeling Fuzzy regression Fuzzy numbers
    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.
    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
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 18756883
    Direcció de correo del autor: jorge.deandres@urv.cat
    Identificador del autor: 0000-0002-7715-779X
    Fecha de alta del registro: 2023-02-18
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Referencia al articulo segun fuente origial: International Journal Of Computational Intelligence Systems. 12 (2): 775-794
    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
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2019
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Computational Mathematics,Computer Science (Miscellaneous),Computer Science, Artificial Intelligence,Computer Science, Interdisciplinary Applications
    Lee–carter model
    Lee-carter model
    Fuzzy-random modelling
    Fuzzy-random modeling
    Fuzzy regression
    Fuzzy numbers
    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
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