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Application of a Power-Exponential Function Based Model to Mortality Rates Forecasting
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. (MAM)ORCID iD: 0000-0003-3204-617X
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. (MAM)
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. (MAM)
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. (MAM)ORCID iD: 0000-0001-9635-0301
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2018 (English)In: Book of Abstracts 5th Stochastic Modeling Techniques and Data Analysis International Conference with Demographics Workshop - SMTDA2018 / [ed] Christos H Skiadas, ISAST: International Society for the Advancement of Science and Technology , 2018Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Mortality rates of living organisms or equipment are modelled in different ways. Variation of mortality over a life span has different characteristics that put constraints and requirements on a model developed to represent it. A well-know problem that complicates modelling of human mortality rates is the "accident hump" occurring in early adulthood. The mortality rate model based on power-exponential functions, previously proposed by the authors, behaves as expected in that life period. Here, it will be compared to other models usually applied in practice and to empirical data. Models will be fitted to known data of measured death rates from many different countries using numerical techniques for curve-fitting with the non-linear least squares method. The properties of the model with respect to quality of fit and usefulness in applications such as insurance pricing or forecasting will be discussed.

Place, publisher, year, edition, pages
ISAST: International Society for the Advancement of Science and Technology , 2018.
Keywords [en]
Mortality rates modelling, power-exponential function, nonlinear curve fitting
National Category
Probability Theory and Statistics Computational Mathematics
Research subject
Mathematics/Applied Mathematics
Identifiers
URN: urn:nbn:se:mdh:diva-41090ISBN: 978-618-5180-27-0 (print)ISBN: 978-618-5180-29-4 (electronic)OAI: oai:DiVA.org:mdh-41090DiVA, id: diva2:1252088
Conference
SMTDA2018 International Conference and Demographics Workshop (12-15 June, 2018), Crete, Greece
Available from: 2018-09-30 Created: 2018-09-30 Last updated: 2018-10-01Bibliographically approved

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http://www.smtda.net/images/Book_of_Abstracts_SMTDA2018_and_Demographics_Workshop-2-6-2018.pdf

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CiteExportLink to record
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  • apa
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Output format
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