Anastasia Kostaki
Javier Moguerza
Alberto Olivares
Stelios Psarakis

http://www.demographic-research.org/volumes/vol20/25/

doi:10.4054/DemRes.2009.20.25

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Abstract
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.

Author's affiliation
Anastasia Kostaki
Athens University of Economics and Business, Greece
Javier Moguerza
Rey Juan Carlos University, Spain
Alberto Olivares
Rey Juan Carlos University, Spain
Stelios Psarakis
Athens University of Economics and Business, Greece

Keywords
age patterns of fertility, graduation techniques, parametric models of fertility, support vector machines

Word count (Main text)
2980

Other articles by the same author/authors (in Demographic Research)

	[16-6] Modeling fertility in modern populations
	[5-1] Expanding an abridged life table

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