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Nonlinear Regression Analysis of the generalized Logistic Model as an Actuarial life contingency model

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dc.contributor.author Kadenova, Aida
dc.contributor.other Wei, Dongming
dc.contributor.other Erlangga, Yogi
dc.date.accessioned 2019-08-08T05:35:59Z
dc.date.available 2019-08-08T05:35:59Z
dc.date.issued 2019-08-08
dc.identifier.citation Kadenova, A. (2019). Nonlinear Regression Analysis of the generalized Logistic Model as an Actuarial life contingency model. Nazarbayev University, School of Science and Technology en_US
dc.identifier.uri http://nur.nu.edu.kz/handle/123456789/4090
dc.description.abstract The aim of this project is to analyze three different population models such as Gompertz, Logistic and Generalized Logistic based USA population data. Finding the appropriate model is essential in actuarial application. Firstly, the parameters of the two models are estimated using the special function ~nls in the R language program. But, due to some complexities, parameters of the generalized logistic model are evaluated using the new method from Causton`s paper. Secondly, two different comparison methods such as residual plot and AIC are used to analyze what model is appropriate for USA statistical data. Lastly, suitable models are used to estimate the force of mortality. en_US
dc.language.iso en en_US
dc.publisher Nazarbayev University School of Science and Technology en_US
dc.rights Attribution-NonCommercial-ShareAlike 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-sa/3.0/us/ *
dc.subject nonlinear regression analysis en_US
dc.subject nonlinear regression en_US
dc.subject regression analysis en_US
dc.title Nonlinear Regression Analysis of the generalized Logistic Model as an Actuarial life contingency model en_US
dc.type Capstone Project en_US
workflow.import.source science


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Attribution-NonCommercial-ShareAlike 3.0 United States Except where otherwise noted, this item's license is described as Attribution-NonCommercial-ShareAlike 3.0 United States