A mortality model based on a mixture distribution function

A new mortality model based on a mixture distribution function is proposed. We mix a half-normal distribution with a generalization of the skew-normal distribution. As a result, we get a six-parameter distribution function that has a good fit with a wide variety of mortality patterns. This mixture m...

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Bibliographic Details
Published in:Population studies 2018-07, Vol.72 (2), p.191-200
Main Authors: Mazzuco, Stefano, Scarpa, Bruno, Zanotto, Lucia
Format: Article
Language:English
Subjects:
accident hump
Accidents
Distribution functions
half-normal distribution
Mathematical models
mixture distribution
Mortality
mortality model
Mortality patterns
Normal distribution
Parameters
Schedules
skew-bimodal-normal distribution
Skewed distributions
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Summary:A new mortality model based on a mixture distribution function is proposed. We mix a half-normal distribution with a generalization of the skew-normal distribution. As a result, we get a six-parameter distribution function that has a good fit with a wide variety of mortality patterns. This mixture model is fitted to several mortality data schedules and compared with the Siler (five-parameter) and Heligman-Pollard (eight-parameter) models. Our proposal serves as a convenient compromise between the Heligman-Pollard model (which ensures a good fit with data but is often overparameterized) and the Siler model (which is more compact but fails to capture 'accident humps').
ISSN:0032-4728
1477-4747
DOI:10.1080/00324728.2018.1439519