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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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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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 |
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QA Mathematics Samsudin, Nurul Syuhada Mohd. Nor, Siti Rohani Multi-population O'Hare with ARIMA, ARIMA-GARCH and ANN in forecasting mortality rate |
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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. |
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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 |
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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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