Spline interpolation of demographic data revisited
Spline functions have been suggested in demographic research for interpolating age-specific data as they have desirablesmoothness optimality properties. However, difficulties arise when boundary conditions need to be satisfied. Anadditional problem is that age-specific demographic data functions are...
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Prince of Songkla University
2011-02-01
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Online Access: | http://rdo.psu.ac.th/sjstweb/journal/33-1/0125-3395-33-1-117-120.pdf |
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doaj-fe76c321a53f490688f4f7489e24c8af2020-11-24T23:51:02ZengPrince of Songkla UniversitySongklanakarin Journal of Science and Technology (SJST)0125-33952011-02-01331117120Spline interpolation of demographic data revisitedAttachai UeranantasunPatarapan OdtonNittaya McNeilSpline functions have been suggested in demographic research for interpolating age-specific data as they have desirablesmoothness optimality properties. However, difficulties arise when boundary conditions need to be satisfied. Anadditional problem is that age-specific demographic data functions are necessarily non-negative, requiring the interpolatingspline to be monotonic non-decreasing. In this paper we describe a simple and effective alternative that circumvents theseproblems. We show that natural cubic splines can be used to interpolate age-specific demographic data and ensure thatrelevant boundary conditions on second derivatives are satisfied, thus preserving the desirable optimality property of theinterpolating function without the need to increase the degree of the spline function. The method involves incorporating oneor two additional strategically placed knots with values estimated from the data. We describe how the method works forselected fertility, population, and mortality data.http://rdo.psu.ac.th/sjstweb/journal/33-1/0125-3395-33-1-117-120.pdfnatural cubic splinemonotonicfertilitypopulationmortality |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Attachai Ueranantasun Patarapan Odton Nittaya McNeil |
spellingShingle |
Attachai Ueranantasun Patarapan Odton Nittaya McNeil Spline interpolation of demographic data revisited Songklanakarin Journal of Science and Technology (SJST) natural cubic spline monotonic fertility population mortality |
author_facet |
Attachai Ueranantasun Patarapan Odton Nittaya McNeil |
author_sort |
Attachai Ueranantasun |
title |
Spline interpolation of demographic data revisited |
title_short |
Spline interpolation of demographic data revisited |
title_full |
Spline interpolation of demographic data revisited |
title_fullStr |
Spline interpolation of demographic data revisited |
title_full_unstemmed |
Spline interpolation of demographic data revisited |
title_sort |
spline interpolation of demographic data revisited |
publisher |
Prince of Songkla University |
series |
Songklanakarin Journal of Science and Technology (SJST) |
issn |
0125-3395 |
publishDate |
2011-02-01 |
description |
Spline functions have been suggested in demographic research for interpolating age-specific data as they have desirablesmoothness optimality properties. However, difficulties arise when boundary conditions need to be satisfied. Anadditional problem is that age-specific demographic data functions are necessarily non-negative, requiring the interpolatingspline to be monotonic non-decreasing. In this paper we describe a simple and effective alternative that circumvents theseproblems. We show that natural cubic splines can be used to interpolate age-specific demographic data and ensure thatrelevant boundary conditions on second derivatives are satisfied, thus preserving the desirable optimality property of theinterpolating function without the need to increase the degree of the spline function. The method involves incorporating oneor two additional strategically placed knots with values estimated from the data. We describe how the method works forselected fertility, population, and mortality data. |
topic |
natural cubic spline monotonic fertility population mortality |
url |
http://rdo.psu.ac.th/sjstweb/journal/33-1/0125-3395-33-1-117-120.pdf |
work_keys_str_mv |
AT attachaiueranantasun splineinterpolationofdemographicdatarevisited AT patarapanodton splineinterpolationofdemographicdatarevisited AT nittayamcneil splineinterpolationofdemographicdatarevisited |
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1725477916824829952 |