Bivariate Copula in Fitting Rainfall Data

被引：8
|
作者：
Yee, Kong Ching [1 ]
Suhaila, Jamaludin [1 ]
Yusof, Fadhilah [1 ]
Mean, Foo Hui [1 ]
机构：
[1] Univ Teknol Malaysia, Fac Sci, Dept Math Sci, Utm Johor Bahru 81310, Johor, Malaysia
来源：
PROCEEDINGS OF THE 21ST NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES (SKSM21): GERMINATION OF MATHEMATICAL SCIENCES EDUCATION AND RESEARCH TOWARDS GLOBAL SUSTAINABILITY | 2014年 / 1605卷
关键词：
Bivariate copula; Rainfall data; Joint distribution; Akaike information criterion (AIC) here;
D O I：
10.1063/1.4887724
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
The usage of copula to determine the joint distribution between two variables is widely used in various areas. The joint distribution of rainfall characteristic obtained using the copula model is more ideal than the standard bivariate modelling where copula is belief to have overcome some limitation. Six copula models will be applied to obtain the most suitable bivariate distribution between two rain gauge stations. The copula models are Ali-Mikhail-Haq (AMH), Clayton, Frank, Galambos, Gumbel-Hoogaurd (GH) and Plackett. The rainfall data used in the study is selected from rain gauge stations which are located in the southern part of Peninsular Malaysia, during the period from 1980 to 2011. The goodness-of-fit test in this study is based on the Akaike information criterion (AIC).
引用
收藏
页码：986 / 990
页数：5
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