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Estimation of a cumulative distribution function under interval censoring ''case 1'' via warped wavelets
Christophe Chesneau 1, Thomas Willer 2
(2012-07-06)

The estimation of an unknown cumulative distribution function in the interval censoring ''case 1'' model from dependent sequences is considered. We construct a new adaptive estimator based on a warped wavelet basis and a hard thresholding rule. Under mild assumptions on the parameters of the model, considering the $\mathbb{L}_2$ risk and the weighted Besov balls, we prove that the estimator attains a sharp rate of convergence. We also investigate its practical performances thanks to simulation experiments.
1:  Laboratoire de Mathématiques Nicolas Oresme (LMNO)
CNRS : UMR6139 – Université de Caen Basse-Normandie
2:  Laboratoire d'Analyse, Topologie, Probabilités (LATP)
CNRS : UMR6632 – Université de Provence - Aix-Marseille I – Université Paul Cézanne - Aix-Marseille III
Mathematics/Statistics

Statistics/Statistics Theory
Adaptive estimation – Strongly mixing – Interval censoring – Warped wavelets – Hard thresholding.
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