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Discrete Beta Kernel Graduation of Age-Specific Demographic Indicators

  • Angelo MazzaEmail author
  • Antonio Punzo
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

Several approaches have been proposed in literature for the kernel graduation of age-specific demographic indicators. Nevertheless, although age is pragmatically a discretized variable with a finite support (typically age at last birthday is considered), commonly used methods employ continuous kernel functions. Moreover, symmetric kernels, that bring in further bias at the support boundaries (the so-called problem of boundary bias), are routinely adopted. In this paper we propose a discrete kernel smooth estimator specifically conceived for the graduation of discrete finite functions, such are age-specific indicators. Kernel functions are chosen from a family of conveniently discretized and re-parameterized beta densities; since their support matches the age range, the issue of boundary bias is eliminated. An application to 1999–2001 mortality data from the Valencia Region (Spain) is also presented.

Keywords

Smoothing Parameter Kernel Estimator Demographic Indicator Symmetric Kernel Beta Density 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.Dipartimento di Impresa, Culture e SocietàUniversità di CataniaCataniaItaly

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