Location- and scale-free procedures for distinguishing between distribution tail models
Fuente:
arXiv
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| Autore principale: | |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| _version_ | 1866909273941868544 |
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| author | Rodionov, Igor |
| author_facet | Rodionov, Igor |
| contents | We consider distinguishing between two distribution tail models when tails of one model are lighter (or heavier) than those of the other. Two procedures are proposed: one scale-free and one location- and scale-free, and their asymptotic properties are established. We show the advantage of using these procedures for distinguishing between certain tail models in comparison with the tests proposed in the literature by simulation and apply them to data on daily precipitation in Green Bay, US and Saentis, Switzerland. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2301_03894 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Location- and scale-free procedures for distinguishing between distribution tail models Rodionov, Igor Statistics Theory Methodology 62G32 We consider distinguishing between two distribution tail models when tails of one model are lighter (or heavier) than those of the other. Two procedures are proposed: one scale-free and one location- and scale-free, and their asymptotic properties are established. We show the advantage of using these procedures for distinguishing between certain tail models in comparison with the tests proposed in the literature by simulation and apply them to data on daily precipitation in Green Bay, US and Saentis, Switzerland. |
| title | Location- and scale-free procedures for distinguishing between distribution tail models |
| topic | Statistics Theory Methodology 62G32 |
| url | https://arxiv.org/abs/2301.03894 |