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