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Modelling residuals dependence in dynamic life tables: A geostatistical approach

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  • Debon, A.
  • Montes, F.
  • Mateu, J.
  • Porcu, E.
  • Bevilacqua, M.

Abstract

The problem of modelling dynamic mortality tables is considered. In this context, the influence of age on data graduation needs to be properly assessed through a dynamic model, as mortality progresses over the years. After detrending the raw data, the residuals dependence structure is analysed, by considering them as a realisation of a homogeneous Gaussian random field defined on . This setting allows for the implementation of geostatistical techniques for the estimation of the dependence and further interpolation in the domain of interest. In particular, a complex form of interaction between age and time is considered, by taking into account a zonally anisotropic component embedded into a nonseparable covariance structure. The estimated structure is then used for prediction of mortality rates, and goodness-of-fit testing is performed through some cross-validation techniques. Comments on validity and interpretation of the results are given.

Suggested Citation

  • Debon, A. & Montes, F. & Mateu, J. & Porcu, E. & Bevilacqua, M., 2008. "Modelling residuals dependence in dynamic life tables: A geostatistical approach," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3128-3147, February.
    • Handle: RePEc:eee:csdana:v:52:y:2008:i:6:p:3128-3147
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    References listed on IDEAS

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    5. David Atance & Ana Debón & Eliseo Navarro, 2020. "A Comparison of Forecasting Mortality Models Using Resampling Methods," Mathematics, MDPI, vol. 8(9), pages 1-21, September.

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