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• W1490996683 abstract "In this work, we study the L p -risk with p ≥ 1 of nonparametric density estimators by using wavelet method in the framework of circular data. In particular, these estimators are based on local hard thresholding techniques; furthermore, they are constructed over the so-called Mexican needlet system, which describes a nearly tight frame over the circle. We prove that these estimators are adaptive and the rates of convergence for their L p -risks are optimal in a class of functional spaces, that is, the Besov spaces, also by means of the concentration properties characterizing the Mexican needlets." @default.
• W1490996683 created "2016-06-24" @default.
• W1490996683 creator A5064142394 @default.
• W1490996683 date "2017-01-01" @default.
• W1490996683 modified "2023-09-24" @default.
• W1490996683 title "Adaptive Density Estimation on the Circle by Nearly Tight Frames" @default.
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• W1490996683 doi "https://doi.org/10.1007/978-3-319-55556-0_13" @default.
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