Yaacob, Nurul Aityqah and Pathmanathan, Dharini and Mohamed, Ibrahim (2022) Extending the GLM framework of the Lee-Carter model with random forest recursive feature elimination based determinants of mortality. Sains Malaysiana, 51 (7). pp. 2237-2247. ISSN 0126-6039, DOI https://doi.org/10.17576/jsm-2022-5107-24.
Full text not available from this repository.Abstract
The Lee-Carter (LC) model led to the development of many prominent mortality models. This study aims to modify the generalised linear model (GLM) (Poisson, negative binomial, and binomial) framework of the LC model by incorporating factors that affect mortality into the model. The top three factors which affect the mortality for each of the 14 countries studied were selected using the random forest recursive feature elimination (RF-RFE) method which eliminates the least important factors based on the correlation of the predictors with the log-mortality rate. These selected factors were integrated in the form of additional bilinear variates to the GLM models and compared to their original counterparts. The RF-RFE method is effective in selecting the best determinants of mortality by avoiding multicollinearity among predictor variables. The inclusion of the time-factor modulation based on the factors selected improved the model adequacy significantly. Vast improvement was evident in the Poisson and binomial settings. Furthermore, the modified GLM version fits short-base-period data well. This study shows that the inclusion of exogenous determinants of mortality improves the performance of the model significantly.
| Item Type: | Article |
|---|---|
| Funders: | University of Malaya , Faculty Research Grant [GPF028B-2018] |
| Uncontrolled Keywords: | GLM; Lee-Carter model; Mortality; Random forest; Recursive feature elimination |
| Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Science |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 28 Aug 2023 07:17 |
| Last Modified: | 28 Aug 2023 07:17 |
| URI: | http://eprints.um.edu.my/id/eprint/40967 |
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