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Regression estimation under strong mixing data

Huijun Guo (guohuijun@emails.bjut.edu.cn) and Youming Liu (liuym@bjut.edu.cn)
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Huijun Guo: Beijing University of Technology
Youming Liu: Beijing University of Technology

Annals of the Institute of Statistical Mathematics, 2019, vol. 71, issue 3, No 4, 553-576

Abstract: Abstract This paper studies multivariate wavelet regression estimators with errors-in-variables under strong mixing data. We firstly prove the strong consistency for non-oscillating and Fourier-oscillating noises. Then, a convergence rate is provided for non-oscillating noises, when an estimated function has some smoothness. Finally, the consistency and convergence rate are discussed for a practical wavelet estimator.

Keywords: Regression estimation; Errors-in-variables; Strong mixing; Practical estimator; Wavelets (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s10463-018-0653-1

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