Publications and Preprints

Nonparametric estimation of two dimensional continuous-discrete density function by wavelets with an application to competing risks
Christophe Chesneau, Isha Dewan and Hassan Doosti
We consider the estimation of a two dimensional continuous-discrete density function with applications to competing risks. We construct two new wavelet estimators (non-adaptive and adaptive) for the joint density function taking into account this special continuous-discrete structure. The rates of convergence of the proposed estimators are established under the $\mathbb{L}_2$ risk over Besov balls. Our main result proves that our adaptive wavelet estimator (based on hard thresholding) attains a sharp rate of convergence. A simulation study illustrates the usefulness of the proposed estimators.

isid/ms/2011/18 [fulltext]

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