Mortality simulations for insured and general populations
Fuente:
arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866913796808769536 |
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| author | Nalmpatian, Asmik Heumann, Christian |
| author_facet | Nalmpatian, Asmik Heumann, Christian |
| contents | This study presents a framework for high-resolution mortality simulations tailored to insured and general populations. Due to the scarcity of detailed demographic-specific mortality data, we leverage Iterative Proportional Fitting (IPF) and Monte Carlo simulations to generate refined mortality tables that incorporate age, gender, smoker status, and regional distributions. This methodology enhances public health planning and actuarial analysis by providing enriched datasets for improved life expectancy projections and insurance product development. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_08814 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Mortality simulations for insured and general populations Nalmpatian, Asmik Heumann, Christian Applications Methodology This study presents a framework for high-resolution mortality simulations tailored to insured and general populations. Due to the scarcity of detailed demographic-specific mortality data, we leverage Iterative Proportional Fitting (IPF) and Monte Carlo simulations to generate refined mortality tables that incorporate age, gender, smoker status, and regional distributions. This methodology enhances public health planning and actuarial analysis by providing enriched datasets for improved life expectancy projections and insurance product development. |
| title | Mortality simulations for insured and general populations |
| topic | Applications Methodology |
| url | https://arxiv.org/abs/2502.08814 |