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Improvement of Fuzzy Mortality Models by Means of Algebraic Methods

Author

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  • Szymański Andrzej
  • Rossa Agnieszka

    (Institute of Statistics and Demography, Warsaw, ; Poland)

Abstract

The forecasting of mortality is of fundamental importance in many areas, such as the funding of public and private pensions, the care of the elderly, and the provision of health service. The first studies on mortality models date back to the 19th century, but it was only in the last 30 years that the methodology started to develop at a fast rate. Mortality models presented in the literature form two categories (see, e.g. Tabeau et al., 2001, Booth, 2006) consisting of the so-called static or stationary models and dynamic models, respectively. Models contained in the first, bigger group contains models use a real or fuzzy variable function with some estimated parameters to represent death probabilities or specific mortality rates. The dynamic models in the second group express death probabilities or mortality rates by means of the solutions of stochastic differential equations, etc.

Suggested Citation

  • Szymański Andrzej & Rossa Agnieszka, 2017. "Improvement of Fuzzy Mortality Models by Means of Algebraic Methods," Statistics in Transition New Series, Polish Statistical Association, vol. 18(4), pages 701-724, December.
    • Handle: RePEc:vrs:stintr:v:18:y:2017:i:4:p:701-724:n:1
    DOI: 10.21307/stattrans-2017-008
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    References listed on IDEAS

    as
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    3. John Wilmoth & Shiro Horiuchi, 1999. "Rectangularization revisited: Variability of age at death within human populations," Demography, Springer;Population Association of America (PAA), vol. 36(4), pages 475-495, November.
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