Wavelet regression estimations for negatively associated sample. Issue 15 (17th November 2020)

• Record Type: Journal Article
• Authors: Guo, Huijun; Kou, Junke
• Is Part Of: Applicable analysis. Volume 99:Issue 15(2020)
• Page Start: 2655
• Page End: 2667
• Publication Date: 2020-11-17
• Subjects: Adrian Muntean; Wavelets -- mean integrated squared error -- nonparametric regression estimation -- negatively associated; 42C40 -- 62G07 -- 62G20; Mathematical analysis -- Periodicals; 515
• DOI: 10.1080/00036811.2019.1577392
• Languages: English
• ISSNs: 0003-6811

Abstract

ABSTRACT: This paper considers wavelet estimations for a regression function based on negatively associated data. We provide upper bounds of mean integrated squared error of wavelet estimators in Besov space. It turns out that our theorem reduces to the theorem of Chesneau and Shirazi [Nonparametric wavelet regression based on biased data. Comm Statist Theory Methods. 2014;43:2642–2658], when the random sample is independent.