Wavelet-based estimators of multivariable mean regression function with long-memory data

Yunzhu He and Dongsheng Wu

Communications in Statistics - Theory and Methods, 2018, vol. 47, issue 10, 2389-2406

Abstract: Wavelet analysis has been proved to be a powerful statistical technique in the non parametric regression. In this paper, we propose non linear wavelet-based estimators for multivariable mean regression function with long-memory data. We also provide an asymptotic expansion for the mean integrated squared error (MISE) of the function estimators. This MISE expansion still works even when the underlying mean regression function is only piecewise smooth. This paper extends the corresponding results in the literature for single variable to multivariable case.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:47:y:2018:i:10:p:2389-2406

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DOI: 10.1080/03610926.2015.1112913

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