Modelling residuals dependence in dynamic life tables: A geostatistical approach
AbstractThe 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.
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Bibliographic InfoArticle provided by Elsevier in its journal Computational Statistics & Data Analysis.
Volume (Year): 52 (2008)
Issue (Month): 6 (February)
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- Rob J. Hyndman & Md. Shahid Ullah, 2005.
"Robust forecasting of mortality and fertility rates: a functional data approach,"
Monash Econometrics and Business Statistics Working Papers
2/05, Monash University, Department of Econometrics and Business Statistics.
- Hyndman, Rob J. & Shahid Ullah, Md., 2007. "Robust forecasting of mortality and fertility rates: A functional data approach," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 4942-4956, June.
- Booth, Heather, 2006. "Demographic forecasting: 1980 to 2005 in review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 547-581.
- Pitacco, Ermanno, 2004. "Survival models in a dynamic context: a survey," Insurance: Mathematics and Economics, Elsevier, vol. 35(2), pages 279-298, October.
- Brouhns, Natacha & Denuit, Michel & Vermunt, Jeroen K., 2002. "A Poisson log-bilinear regression approach to the construction of projected lifetables," Insurance: Mathematics and Economics, Elsevier, vol. 31(3), pages 373-393, December.
- Gavin, John & Haberman, Steven & Verrall, Richard, 1993. "Moving weighted average graduation using kernel estimation," Insurance: Mathematics and Economics, Elsevier, vol. 12(2), pages 113-126, April.
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