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N-W Kernel Regression Estimation for Correlation Function of Bivariate Extremes Copula Function

This paper gives an estimate of correlation function for bivariate extremes Copula model using kernel regression method. A N-W kernel regression estimator is constructed and we prove that the estimator is asymptotically unbiased. Based on selection of the optimal bandwidth, we compare the N-W kernel regression estimation and OLS estimation by numerical simulation. The result shows that the N-W kernel regression estimator is more stable than the OLS estimator. So, the N-W kernel regression estimation is a relatively favourable non-parametric method.