Multi-population O'Hare with ARIMA, ARIMA-GARCH and ANN in forecasting mortality rate

Multi-population mortality model has gained attention from prominent researchers of mortality due to its ability to provide biologically reasonable forecast. Previously, many researchers have proposed several multi-population stochastic mortality models that they considered adequate to produce accur...

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Main Authors: Samsudin, Nurul Syuhada, Mohd. Nor, Siti Rohani
Format: Article
Language:English
Published: Penerbit UTM Press 2023
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Online Access:http://eprints.utm.my/105447/1/SitiRohaniMohd2023_MultiPopulationOHarewithARIMAARIMAGARCH.pdf
http://eprints.utm.my/105447/
http://dx.doi.org/10.11113/matematika.v39.n3.1496
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Institution: Universiti Teknologi Malaysia
Language: English
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spelling my.utm.1054472024-04-30T07:19:34Z http://eprints.utm.my/105447/ Multi-population O'Hare with ARIMA, ARIMA-GARCH and ANN in forecasting mortality rate Samsudin, Nurul Syuhada Mohd. Nor, Siti Rohani QA Mathematics Multi-population mortality model has gained attention from prominent researchers of mortality due to its ability to provide biologically reasonable forecast. Previously, many researchers have proposed several multi-population stochastic mortality models that they considered adequate to produce accurate life expectancy. However, little have been addressed of the variability in full ages and time, which can contribute to an erroneous estimation of life expectancy. Therefore, this study proposed a new multi-population O'Hare with ARIMA, ARIMA-GARCH and ANN in forecasting the mortality rate for male and female in Malaysia, Taiwan, Japan, Hong Kong, Australia, USA, UK, Canada, and Switzerland. Multi-population O'Hare was used as a reference model, whilst ARIMA, ARIMA-GARCH and ANN were incorporated to the reference model to forecast the mortality rates. The adequacy of the proposed model was assessed by using measurement errors which were Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE). The results showed by multi-population O'Hare with ARIMA-GARCH gave the best forecasting performance for Taiwan, Japan, Australia, USA, UK, Canada, and Switzerland. On the other hand, multi-population O'Hare with ARIMA gave the best forecasting performance for Malaysia, whereas multi-population O'Hare with ANN gave the best forecasting performance for Hong Kong. Penerbit UTM Press 2023-12 Article PeerReviewed application/pdf en http://eprints.utm.my/105447/1/SitiRohaniMohd2023_MultiPopulationOHarewithARIMAARIMAGARCH.pdf Samsudin, Nurul Syuhada and Mohd. Nor, Siti Rohani (2023) Multi-population O'Hare with ARIMA, ARIMA-GARCH and ANN in forecasting mortality rate. MATEMATIKA, 39 (3). pp. 213-226. ISSN 0127-8274 http://dx.doi.org/10.11113/matematika.v39.n3.1496 DOI:10.11113/matematika.v39.n3.1496
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic QA Mathematics
spellingShingle QA Mathematics
Samsudin, Nurul Syuhada
Mohd. Nor, Siti Rohani
Multi-population O'Hare with ARIMA, ARIMA-GARCH and ANN in forecasting mortality rate
description Multi-population mortality model has gained attention from prominent researchers of mortality due to its ability to provide biologically reasonable forecast. Previously, many researchers have proposed several multi-population stochastic mortality models that they considered adequate to produce accurate life expectancy. However, little have been addressed of the variability in full ages and time, which can contribute to an erroneous estimation of life expectancy. Therefore, this study proposed a new multi-population O'Hare with ARIMA, ARIMA-GARCH and ANN in forecasting the mortality rate for male and female in Malaysia, Taiwan, Japan, Hong Kong, Australia, USA, UK, Canada, and Switzerland. Multi-population O'Hare was used as a reference model, whilst ARIMA, ARIMA-GARCH and ANN were incorporated to the reference model to forecast the mortality rates. The adequacy of the proposed model was assessed by using measurement errors which were Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE). The results showed by multi-population O'Hare with ARIMA-GARCH gave the best forecasting performance for Taiwan, Japan, Australia, USA, UK, Canada, and Switzerland. On the other hand, multi-population O'Hare with ARIMA gave the best forecasting performance for Malaysia, whereas multi-population O'Hare with ANN gave the best forecasting performance for Hong Kong.
format Article
author Samsudin, Nurul Syuhada
Mohd. Nor, Siti Rohani
author_facet Samsudin, Nurul Syuhada
Mohd. Nor, Siti Rohani
author_sort Samsudin, Nurul Syuhada
title Multi-population O'Hare with ARIMA, ARIMA-GARCH and ANN in forecasting mortality rate
title_short Multi-population O'Hare with ARIMA, ARIMA-GARCH and ANN in forecasting mortality rate
title_full Multi-population O'Hare with ARIMA, ARIMA-GARCH and ANN in forecasting mortality rate
title_fullStr Multi-population O'Hare with ARIMA, ARIMA-GARCH and ANN in forecasting mortality rate
title_full_unstemmed Multi-population O'Hare with ARIMA, ARIMA-GARCH and ANN in forecasting mortality rate
title_sort multi-population o'hare with arima, arima-garch and ann in forecasting mortality rate
publisher Penerbit UTM Press
publishDate 2023
url http://eprints.utm.my/105447/1/SitiRohaniMohd2023_MultiPopulationOHarewithARIMAARIMAGARCH.pdf
http://eprints.utm.my/105447/
http://dx.doi.org/10.11113/matematika.v39.n3.1496
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