Bivariate copula in Johor rainfall data
Copula is a probability distribution that allows a joint distribution function build from different univariate marginal distribution function. The climate in Malaysia is very humid, which cause the rainfall data is usually skewed. Gumbel, Clayton and skew t copula are distributions that good in anal...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Published: |
American Institute of Physics Inc.
2016
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/73204/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-84984585617&doi=10.1063%2f1.4954624&partnerID=40&md5=a9da09bf40eea8179ca035303db82b85 |
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| Institution: | Universiti Teknologi Malaysia |
| Summary: | Copula is a probability distribution that allows a joint distribution function build from different univariate marginal distribution function. The climate in Malaysia is very humid, which cause the rainfall data is usually skewed. Gumbel, Clayton and skew t copula are distributions that good in analyze data that is extreme. Five rain gauge stations in Johor will be used in this study. The most suitable copula function that best suit the bivariate relation among the five stations will be studied. The Akaike information criterion and Bayesian information criterion will be the used as the moderators to decide the best suit copula function. Gumbel copula is the best suit copula function among the five rain gauge stations. |
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