Logistic and CSG Growth Models for Predicting Life Expectancy

Year 2024, Volume: 29 Issue: 2, 503 - 513, 31.08.2024

Begüm Çığşar , Deniz Ünal , Abdel-hack Bıo Boulou , Bassel Alshahaby

https://doi.org/10.53433/yyufbed.1432156

Abstract

The tables that allow calculating the probability of death at a certain age by recording the number of births/deaths in a population are called life tables. The concept of life expectancy, which is a measure that determines how long a creature will live, is also determined by mortality rates obtained from life tables. It is also possible to model the expected lifetime with some nonlinear mathematical functions. One of the functions that is often used in modeling mortality rates is the logistic growth function. This study aims to propose a model that can be used as an alternative to the logistic growth model and to interpret the mortality rates of countries. In this study, the life expectancy of males and females in Türkiye, Singapore, Norway, and China was modeled using the logistic and the CSG growth model, which was newly introduced to the literature. When modeling the life expectancy of countries, the adjusted graph was drawn following the data of each growth model. Then, the performances of the logistic growth model and the CSG growth model were compared with R^2, RMSE, and MAPE statistical criteria. As a result of the comparison, it was revealed that the CSG growth model is more suitable than the logistic model for estimating life expectancy for overall data and for each gender. The originality of this study is the CSG model which is a new nonlinear model that predicts life expectancy effectively for related datasets.

Keywords

CSG model, Growth models, Life expectancy, Life tables, Logistic model

Project Number

FBA-2022-14131

Yaşam Beklentisi Tahmininde Lojistik ve CSG Modelleri

Abstract

Bir popülasyondaki doğum/ölüm sayıları kullanılarak belirli bir yaştaki ölüm olasılığının hesaplanmasını sağlayan tablolara yaşam tabloları denir. Bir canlının ne kadar yaşayıp yaşamayacağının ölçüsü olan yaşam beklentisi, yaşam tablolarından elde edilen ölüm oranıyla hesaplanmaktadır. Beklenen yaşam süresini, lineer olmayan fonksiyonlarla modellemek mümkündür. Ölüm oranlarının modellenmesinde sıklıkla kullanılan fonksiyonlardan biri lojistik büyüme modelidir. Bu çalışma ile lojistik büyüme modeline alternatif olarak kullanılabilecek literatüre yeni kazandırılan bir model kullanarak Türkiye, Singapur, Norveç ve Çin’e ait ölüm oranlarını yorumlamak amaçlanmıştır. Ülkelerin total ve cinsiyete göre yaşam beklentileri lojistik ve CSG büyüme modelleri kullanılarak tahmin edilmiştir. Ülkelerin yaşam beklentileri tahmin edilirken her büyüme modelinin tahmini grafiklerle desteklenmiştir. Daha sonra lojistik ve CSG büyüme modellerinin performansları R^2, RMSE ve MAPE istatistikleri kullanılarak karşılaştırılmıştır Karşılaştırma sonucunda CSG büyüme modelinin yaşam beklentisi tahmininde hem total veri hem de cinsiyetler açısından lojistik büyüme modeline göre daha iyi tahminde bulunduğu tespit edilmiştir. Bu çalışmanın özgünlüğü, çalışmada kullanılan veri kümeleri için yaşam beklentisini etkili bir şekilde tahmin edebilen yeni bir doğrusal olmayan büyüme modelinin sunulmasıdır.

Keywords

Büyüme modelleri, CSG modeli, Lojistik model, Yaşam beklentisi, Yaşam tabloları

Supporting Institution

Çukurova Üniversitesi

Project Number

FBA-2022-14131

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