A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Linear wavelet estimation of the derivatives of a regression function based on biased data
2016
Communications in Statistics - Theory and Methods
Preserved Fulltext
This paper deals with the problem of estimating the derivatives of a regression function based on biased data. We develop two different linear wavelet estimators according to the knowledge of the "biased density" of the design. The new estimators are analyzed with respect to their L p risk with p ≥ 1 over Besov balls. Fast polynomial rates of convergence are obtained.
doi:10.1080/03610926.2016.1213287
fatcat:zfn7lk6kpnbxhjghgnjkrh7dpy