An extension of Chesneau’s theorem

Junke Kou and Youming Liu

Statistics & Probability Letters, 2016, vol. 108, issue C, 23-32

Abstract: This paper considers a lower bound estimation over Lp(Rd)(1≤p<∞) risk for d dimensional regression functions in Besov spaces based on biased data. We provide the best possible lower bound up to a lnn factor by using wavelet methods. When the weight function ω(x,y)≡1 and d=1, our result reduces to Chesneau’s theorem, see Chesneau (2007).

Keywords: Lower bound; Biased regression estimation; Lp risk; Wavelets (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.spl.2015.09.018

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