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Graduating the age-specific fertility pattern using Support Vector Machines

Listed author(s):
  • Anastasia Kostaki

    (Athens University of Economics and Business)

  • Javier Moguerza

    (Universidad Rey Juan Carlos)

  • Alberto Olivares

    (Universidad Rey Juan Carlos)

  • Stelios Psarakis

    (Athens University of Economics and Business)

Registered author(s):

    A topic of interest in demographic literature is the graduation of the age-specific fertility pattern. A standard graduation technique extensively used by demographers is to fit parametric models that accurately reproduce it. Non-parametric statistical methodology might be alternatively used for this graduation purpose. Support Vector Machines (SVM) is a non-parametric methodology that could be utilized for fertility graduation purposes. This paper evaluates the SVM techniques as tools for graduating fertility rates In that we apply these techniques to empirical age specific fertility rates from a variety of populations, time period, and cohorts. Additionally, for comparison reasons we also fit known parametric models to the same empirical data sets.

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    Article provided by Max Planck Institute for Demographic Research, Rostock, Germany in its journal Demographic Research.

    Volume (Year): 20 (2009)
    Issue (Month): 25 (June)
    Pages: 599-622

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    Handle: RePEc:dem:demres:v:20:y:2009:i:25
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    1. Pearce, N.D. & Wand, M.P., 2006. "Penalized Splines and Reproducing Kernel Methods," The American Statistician, American Statistical Association, vol. 60, pages 233-240, August.
    2. Carl Schmertmann, 2003. "A system of model fertility schedules with graphically intuitive parameters," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 9(5), pages 81-110, October.
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