Modelling temperature measurement data by using copula functions

Authors : Ayşe METİN KARAKAŞ

Pages : 27-32

Doi:10.17678/beuscitech.322140

View : 17 | Download : 9

Publication Date : 2017-06-13

Article Type : Research Paper

Abstract :  In this study, methods of copula estimation are used and the temperature measurement data of the four regions located at the same positions in the range of 01.01.2008 - 30.04.2009 was modeled with copula functions. For dependence structures of the data sets, it is calculated Kendall Tau and Spearman Rho values which are nonparametric. Based on this method, parameters of copula are obtained. A clear advantage of the copula-based model is that it allows for maximum-likelihood estimation using all available data. The main aim of the method is to find the parameters that make the likelihood functions get its maximum value. With the help of the maximum-likelihood estimation method, for copula families, it is obtained likelihood values. These values, Akaike information criteria insert ignore into journalissuearticles values(AIC); are used to determine which copula supplies the suitability for the data set.
Keywords : Copula function, Archimedean copula function, Kendall tau, Spearman rho, Temperature