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Comparison analysis of copula function of precipitation and wind speed in Korean Peninsula
Journal of the Korean Data & Information Science Society 2018;29:609-20
Published online May 31, 2018
© 2018 Korean Data and Information Science Society.

Taeyong Kwon1 · Sanghoo Yoon2

1Department of Statistics, Daegu University
2Division of Mathematics and Big Data Science, Daegu University
Correspondence to: assistant professor, Division of Mathematics and big data science, Daegu University, Gyeongbuk 38453, Republic of Korea. E-mail: statstar@daegu.ac.kr
Received March 30, 2018; Revised May 18, 2018; Accepted May 21, 2018.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Natural disasters cause enormous damage socially and economically. In order to understand the complex dependence structure between precipitation and wind speed, we estimated the bivariate copula function by analyzing the correlation between precipitation and wind speed. The copula function estimates the joint probability distribution which is difficult to calculate mathematically. In this study, we carried out analysis using data of daily precipitation and wind speed collected from 61 weather stations from 1973 to 2016. Generalized Pareto, Log-Normal, Gamma, Weibull, Cauchy, Exponential distribution were considered to explain marginal distributions of the copula function. The dependency between the marginal distributions was calculated by Kendall’s Tau and Spearman’s rho. Elliptical, Archimedean, and extreme copula family were used to estimate the bivariate copula function between precipitation and wind speed. We conducted that there was dependence between precipitation and wind speed in Gangneung, Pohang, Jeju, Buyeo, and Yeongdeok. The parameters of copula functions were estimated with maximum pseudo likelihood and goodness of fit test was performed. Joe copula (Gangneung), Frank copula (Pohang), Husler-Reiss copula (Jeju and Yeongdeok), and Galambos copula (Buyeo) were selected as the optimal copula function.
Keywords : Copula, precipitation, pseudo data, wind speed