Rydén, Jesper
(2019).
A note on analysis of extreme minimum temperatures with the GAMLSS framework.
Acta Geophysica. 67
, 1599-1604
[Journal article]
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Abstract
Estimation of return levels, based on extreme value distributions, is of importance in the earth and environmental sciences. To incorporate non-stationarity in the modelling, the statistical framework of generalised additive models for location, scale and shape is an option, providing flexibility and with a wide range of distributions implemented. With a large set of selections possible, model choice is an issue. As a case study, we investigate annual minimum temperatures from measurements at a location in northern Sweden. For practical work, it turns out that care must be taken in examining the obtained distributions, not solely relying on information criteria. A simulation study illustrates the findings.
| Authors/Creators: | Rydén, Jesper | ||||
|---|---|---|---|---|---|
| Title: | A note on analysis of extreme minimum temperatures with the GAMLSS framework | ||||
| Series Name/Journal: | Acta Geophysica | ||||
| Year of publishing : | 2019 | ||||
| Volume: | 67 | ||||
| Page range: | 1599-1604 | ||||
| Number of Pages: | 6 | ||||
| Publisher: | Springer | ||||
| ISSN: | 1895-6572 | ||||
| Language: | English | ||||
| Publication Type: | Journal article | ||||
| Refereed: | Yes | ||||
| Article category: | Scientific peer reviewed | ||||
| Version: | Published version | ||||
| Copyright: | Creative Commons: Attribution 4.0 | ||||
| Full Text Status: | Public | ||||
| Subjects: | (A) Swedish standard research categories 2011 > 1 Natural sciences > 101 Mathematics > 10106 Probability Theory and Statistics (A) Swedish standard research categories 2011 > 1 Natural sciences > 105 Earth and Related Environmental Sciences > Oceanography, Hydrology, Water Resources | ||||
| Keywords: | GEV distribution, GAMLSS, Non-stationary models, Extreme temperatures, Model selection | ||||
| URN:NBN: | urn:nbn:se:slu:epsilon-p-103415 | ||||
| Permanent URL: | http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-103415 | ||||
| Additional ID: |
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| ID Code: | 16566 | ||||
| Faculty: | NJ - Fakulteten för naturresurser och jordbruksvetenskap | ||||
| Department: | (NL, NJ) > Dept. of Energy and Technology | ||||
| Deposited By: | SLUpub Connector | ||||
| Deposited On: | 20 Feb 2020 08:25 | ||||
| Metadata Last Modified: | 20 Feb 2020 08:25 |
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