ENBIS-8 in Athens

21 – 25 September 2008 Abstract submission: 14 March – 11 August 2008

Modeling Mortality Pattern using Support Vector Machines

22 September 2008, 11:55 – 11:59


Submitted by
Alberto Olivares
Anastasia Kostaki , Javier M. Moguerza , Alberto Olivares , Stelios Psarakis
Dept. of Statistics, Athens University of Economics and Business & Dept. of Statistics and Operational Research, Rey Juan Carlos University (Spain)
A topic of interest in process modeling, in particular for demographic, biostatistical analysis as well as in actuarial practice is the graduation of the age-specific mortality pattern. A classical graduation technique extensively used by demographers and actuaries is to fit parametric models that accurately reproduce it. Recently, particular emphasis is given in graduation using non parametric techniques such as kernel estimators. Support Vector Machines (SVM) is an alternative methodology that could be utilized for mortality graduation purposes. This paper evaluates the SVM techniques as tools for graduating mortality rates. In that we apply this methodology to empirical death rates from a variety of populations and time periods. Additionally, for comparison reasons we also apply kernel techniques and fit the Heligman-Pollard model to the same empirical data sets.

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