CHINESE JOURNAL OF APPLIED PROBABILITY AND STATIST 2009, 25(4) 421-432 DOI:      ISSN: 1001-4268 CN: 31-1256

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Keywords
Varying-coefficient models
wavelet
least-square estimation
asymptotic normality
convergence rate.
Authors
Lu Yiqiang
Li Zhilin
PubMed
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Wavelet Estimation in Varying-Coefficient Models

Lu Yiqiang,Li Zhilin

Institute of Electronic Technology, the PLA Information Engineering University

Abstract��

This paper is concerned with the estimation
of varying-coefficient model that is frequently used in statistical
modeling. The wavelet procedures are developed to estimate the
coefficient functions. The advantage of this approach is to avoid
the restrictive smoothness requirement for nonparametric function of
the traditional smoothing approaches for varying-coefficient model,
such as kernel and local polynomial methods. Furthermore, the
convergence rate of the wavelet estimators is derived and the
asymptotic normality is established. Finite sample properties are
studied through Monte Carlo simulations.

Keywords�� Varying-coefficient models   wavelet   least-square estimation   asymptotic normality   convergence rate.  
Received 1900-01-01 Revised 1900-01-01 Online:  
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Corresponding Authors: Lu Yiqiang
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