Wavelet estimation of copula function based on censored data
Bahareh Ghanbari, Masoud Yarmohammadi, Nargess Hosseinioun, Esmaeil Shirazi · Journal of Inequalities and Applications · 2019
In this paper, we consider wavelet analysis to obtain an estimator of a copula function based on censored data. We show that optimal convergence rates for the mean integrated squared error (MISE) of linear wavelet-based function estimators are exact under right censoring model. Moreover, we derive asymptotic formulae for MISE. Finally, the simulation results and the analysis of real data validate the proposed procedure.