The Tweedie Index Parameter and Its Estimator: An Introduction with Applications to Actuarial Ratemaking
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| dc.contributor.author | Temple, Seth David | |
| dc.date.accessioned | 2023-10-25T19:06:52Z | |
| dc.date.available | 2023-10-25T19:06:52Z | |
| dc.date.issued | 2018-06 | |
| dc.description | 87 pages | en_US |
| dc.description.abstract | Tweedie random variables are exponential dispersion models that have power unit variance functions, are infnitely divisible, and are closed under translations and scale transformations. Notably, a Tweedie random variable has an indexing/power param- eter that is key in describing its distribution. Actuaries typically set this parameter to a default value, whereas R's tweedie package provides tools to estimate the Tweedie power via maximum likelihood estimation. This estimation is tested on simulations and applied to an auto severity dataset and a home loss cost dataset. Models built with an estimated Tweedie power observe lower Akaike Information Criterion rela- tive to models built with default Tweedie powers. However, this parameter tuning only marginally changes regression coefficients and model predictions. Given time constraints, we recommend actuaries use default Tweedie powers and consider alter- native feature engineering. | en_US |
| dc.identifier.uri | https://hdl.handle.net/1794/29040 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | University of Oregon | en_US |
| dc.rights | Creative Commons BY-NC-ND 4.0-US | en_US |
| dc.title | The Tweedie Index Parameter and Its Estimator: An Introduction with Applications to Actuarial Ratemaking | en_US |
| dc.type | Thesis / Dissertation | en_US |