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• W2283082903 abstract "We consider the problem of estimating an unknown density and its derivatives in a regression setting with random design. Instead of expanding the function on a regular wavelet basis, we expand it on the basis , a warped wavelet basis. We investigate the properties of this new basis and evaluate its asymptotic performance by determining an upper bound of the mean integrated squared error under different dependence structures. We prove that it attains a sharp rate of convergence for a wide class of unknown regression functions." @default.
• W2283082903 created "2016-06-24" @default.
• W2283082903 creator A5076828422 @default.
• W2283082903 date "2016-01-01" @default.
• W2283082903 modified "2023-10-16" @default.
• W2283082903 title "Estimation of Regression Function for Nonequispaced Samples Based on Warped Wavelets" @default.
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• W2283082903 doi "https://doi.org/10.4236/ojs.2016.61008" @default.
• W2283082903 hasPublicationYear "2016" @default.
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