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dc.contributor.advisor Peiris, TSG
dc.contributor.author Jayatilake, AC
dc.date.accessioned 2018-06-20T22:23:09Z
dc.date.available 2018-06-20T22:23:09Z
dc.identifier.uri http://dl.lib.mrt.ac.lk/handle/123/13211
dc.description.abstract Population ageing is an universal phenomenon and it is expected to be among the most prominent global demographic trends of the 21st century. In Sri Lanka there was a rising trend of ageing population throughout the past years and has recorded the highest number of agers within South Asia. However, no sound statistical or mathematical models were developed to project ageing population in Sri Lanka. Using the population aged 60 years and above in Sri Lanka during 1950-2016, three types of statistical models: (i) ARIMA (0, 2, 1), (ii) growth model, and (iii) double exponential smoothing model were developed. The models were compared using various statistical indicators and some statistical diagnostics tests. The comparison was done for both training set as well as validation set. Among these models the double exponential smoothing model was found as the best fitted model. According to the forecast derived from the best fitted model, it was found that the increasing trend of ageing population in the country will continue in the future and there will be approximately 2,936,000 ageing population in Sri Lanka in 2020. The information obtained in this study is beneficial for planners and decision makers in the government sector and other relevant organizations to cater to the needs of the increasing agers in the future of Sri Lanka. en_US
dc.language.iso en en_US
dc.subject Ageing Population en_US
dc.subject ARIMA en_US
dc.subject Demographic en_US
dc.subject Exponential Smoothing en_US
dc.title Modeling ageing population in Sri Lanka towards better care for elderly en_US
dc.type Thesis-Abstract en_US
dc.identifier.faculty Engineering en_US
dc.identifier.degree Master of Science in Business Statistics en_US
dc.identifier.department Department of Mathematics en_US
dc.date.accept 2017-07
dc.identifier.accno TH3421 en_US


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