Generating monthly rainfall amount using multivariate skew-t copula

This study aims to generate rainfall data in cases where the data is not available or not enough for a certain area of study. In general, the rainfall data is rightly skewed, so the multivariate skew-t copula is used as it able to model rainfall amount and capture the spatial dependence in the data....

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Main Authors:	Noor Fadhilah, Ahmad Radi, Roslinazairimah, Zakaria, Siti Zanariah, Satari
Format:	Conference or Workshop Item
Language:	English
Published:	IOP Publishing 2017
Subjects:	T Technology (General)
Online Access:	http://umpir.ump.edu.my/id/eprint/22306/ http://umpir.ump.edu.my/id/eprint/22306/ http://umpir.ump.edu.my/id/eprint/22306/1/Generating%20monthly%20rainfall%20amount%20using%20multivariate.pdf

id	ump-22306
recordtype	eprints
spelling	ump-223062018-10-03T03:46:46Z http://umpir.ump.edu.my/id/eprint/22306/ Generating monthly rainfall amount using multivariate skew-t copula Noor Fadhilah, Ahmad Radi Roslinazairimah, Zakaria Siti Zanariah, Satari T Technology (General) This study aims to generate rainfall data in cases where the data is not available or not enough for a certain area of study. In general, the rainfall data is rightly skewed, so the multivariate skew-t copula is used as it able to model rainfall amount and capture the spatial dependence in the data. To illustrate the methodology, three rainfall stations in Kelantan are used. Firstly, the observed data is transformed to uniform unit. The Spearman's correlation coefficient is calculated between the three stations. It is found that the correlations between the stations are significance at α = 0.05. The next step involved generating the synthetic rainfall data using the multivariate skew-t copula. The data is then transformed to uniform unit and the correlation coefficient is calculated for the generated data. Finally, the correlation coefficient of the observed and the generated data are compared. The Kolmogorov-Smirnov goodness of fit test is used to assess the fit between theoretical and empirical copula and supported by graphical representation. The results show that there is no significant difference between empirical and theoretical copula at 5% significance level. Thus, the multivariate skew-t copula is suitable to generate synthetic rainfall data that can mimic the observed rainfall data. It can also be used to present different rainfall scenarios by changing the value of the parameters in the model IOP Publishing 2017 Conference or Workshop Item PeerReviewed pdf en cc_by http://umpir.ump.edu.my/id/eprint/22306/1/Generating%20monthly%20rainfall%20amount%20using%20multivariate.pdf Noor Fadhilah, Ahmad Radi and Roslinazairimah, Zakaria and Siti Zanariah, Satari (2017) Generating monthly rainfall amount using multivariate skew-t copula. In: Journal of Physics: Conference Series, 1st International Conference on Applied & Industrial Mathematics and Statistics 2017 (ICoAIMS 2017), 8-10 August 2017 , Kuantan, Pahang, Malaysia. pp. 1-7., 890 (012133). ISSN 1742-6588 https://doi.org/10.1088/1742-6596/890/1/012133
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	T Technology (General)
spellingShingle	T Technology (General) Noor Fadhilah, Ahmad Radi Roslinazairimah, Zakaria Siti Zanariah, Satari Generating monthly rainfall amount using multivariate skew-t copula
description	This study aims to generate rainfall data in cases where the data is not available or not enough for a certain area of study. In general, the rainfall data is rightly skewed, so the multivariate skew-t copula is used as it able to model rainfall amount and capture the spatial dependence in the data. To illustrate the methodology, three rainfall stations in Kelantan are used. Firstly, the observed data is transformed to uniform unit. The Spearman's correlation coefficient is calculated between the three stations. It is found that the correlations between the stations are significance at α = 0.05. The next step involved generating the synthetic rainfall data using the multivariate skew-t copula. The data is then transformed to uniform unit and the correlation coefficient is calculated for the generated data. Finally, the correlation coefficient of the observed and the generated data are compared. The Kolmogorov-Smirnov goodness of fit test is used to assess the fit between theoretical and empirical copula and supported by graphical representation. The results show that there is no significant difference between empirical and theoretical copula at 5% significance level. Thus, the multivariate skew-t copula is suitable to generate synthetic rainfall data that can mimic the observed rainfall data. It can also be used to present different rainfall scenarios by changing the value of the parameters in the model
format	Conference or Workshop Item
author	Noor Fadhilah, Ahmad Radi Roslinazairimah, Zakaria Siti Zanariah, Satari
author_facet	Noor Fadhilah, Ahmad Radi Roslinazairimah, Zakaria Siti Zanariah, Satari
author_sort	Noor Fadhilah, Ahmad Radi
title	Generating monthly rainfall amount using multivariate skew-t copula
title_short	Generating monthly rainfall amount using multivariate skew-t copula
title_full	Generating monthly rainfall amount using multivariate skew-t copula
title_fullStr	Generating monthly rainfall amount using multivariate skew-t copula
title_full_unstemmed	Generating monthly rainfall amount using multivariate skew-t copula
title_sort	generating monthly rainfall amount using multivariate skew-t copula
publisher	IOP Publishing
publishDate	2017
url	http://umpir.ump.edu.my/id/eprint/22306/ http://umpir.ump.edu.my/id/eprint/22306/ http://umpir.ump.edu.my/id/eprint/22306/1/Generating%20monthly%20rainfall%20amount%20using%20multivariate.pdf
first_indexed	2023-09-18T22:33:08Z
last_indexed	2023-09-18T22:33:08Z
_version_	1777416418836348928

Generating monthly rainfall amount using multivariate skew-t copula

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