| Issue |
ITM Web Conf.
Volume 36, 2021
The 16th IMT-GT International Conference on Mathematics, Statistics and their Applications (ICMSA 2020)
|
|
|---|---|---|
| Article Number | 01007 | |
| Number of page(s) | 9 | |
| Section | Statistics and Data Science | |
| DOI | https://doi.org/10.1051/itmconf/20213601007 | |
| Published online | 26 January 2021 | |
Modelling extreme precipitation: an application to two selected rainfall stations in Malaysia
1
Department of Mathematical and Actuarial Sciences, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, 43000 Kajang, Selangor, Malaysia
2
Institute of Mathematical Sciences, Faculty of Science, University of Malaya, 50603 Kuala Lumpur, Malaysia
3
Mathematics Division, Centre for Foundation Studies in Science, University of Malaya, 50603 Kuala Lumpur, Malaysia
* Corresponding author: aidaadha@utar.edu.my
Statistical models of rainfall have been applied in the understanding of the rainfall past trends, identifying for any anomalies, and making projections of future climate change in Malaysia. Herein, we analyse the rainfall data of 7-year period using the gamma and beta regression models to fit Malaysian extreme precipitation events of two stations, each in the West Coast region and the East Coast region, with extreme precipitation calendar date (in the angular form) as the predictor of the models. While the significance test as the p-value is much less than 0.05, it shows that there is a significant relationship between the climatology response variables. The deviance residual plot will be used to check the goodness of fit for diagnostic checking. The results show the models are useful in highlighting the latest trends and projections of climate change in Malaysia.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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