nonparametric estimation of copula density under bias and multiplicative censoring via wavelet methods

The copula density estimation problem under bias and multiplicative censoring is considered. adopting the wavelet approach, we construct a linear nonadaptive estimator and a non-linear adaptive estimator. the adaptive one belongs to the family of the hard thresholding estimators. we evaluate their performances by determining upper bounds of the mean integrated squared error over a wide range of functions. sharp upper bounds are obtained.