Adaptive wavelet estimation of a density from mixtures under multiplicative censoring |
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| Authors: | Yogendra P. Chaubey Christophe Chesneau Hassan Doosti |
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| Affiliation: | 1. Department of Mathematics and Statistics, Concordia University, Montréal, QC, Canada H3G 1M8chaubey@alcor.concordia.ca;3. Laboratoire de Mathématiques Nicolas Oresme, Université de Caen BP 5186, F 14032 Caen Cedex, France;4. Department of Mathematics, Kharazmi University, Tehran, Iran;5. Department of Mathematics and Statistics, The University of Melbourne, Melbourne, Australia |
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| Abstract: | In this paper, a mixture model under multiplicative censoring is considered. We investigate the estimation of a component of the mixture (a density) from the observations. A new adaptive estimator based on wavelets and a hard thresholding rule is constructed for this problem. Under mild assumptions on the model, we study its asymptotic properties by determining an upper bound of the mean integrated squared error over a wide range of Besov balls. We prove that the obtained upper bound is sharp. |
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| Keywords: | 62G07 62G20 60K35 |
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