BOOTSTRAP WAVELET IN THE NONPARAMETRIC REGRESSION MODEL WITH WEAKLY DEPENDENT PROCESSES

数学物理学报(英文版) ›› 2004, Vol. 24 ›› Issue (1): 61-70.

BOOTSTRAP WAVELET IN THE NONPARAMETRIC REGRESSION MODEL WITH WEAKLY DEPENDENT PROCESSES

林路,张润楚

2.School of Mathematics and System Sciences, Shandong University, Jinan 250100, China
3.School of Mathematical Sciences, Nankai University, Tianjin 300071, China

出版日期:2004-07-13 发布日期:2004-07-13
基金资助:
This paper is supported by NNSF project (10371059) of
China and Youth Teacher Foundation of Nankai University.

BOOTSTRAP WAVELET IN THE NONPARAMETRIC REGRESSION MODEL WITH WEAKLY DEPENDENT PROCESSES

LIN Lu, ZHANG Run-Chu

Online:2004-07-13 Published:2004-07-13
Supported by:
This paper is supported by NNSF project (10371059) of
China and Youth Teacher Foundation of Nankai University.

摘要/Abstract

摘要：

This paper introduces a method of bootstrap wavelet estimation in a non-
parametric regression model with weakly dependent processes for both fixed and random
designs. The asymptotic bounds for the bias and variance of the bootstrap wavelet estima-
tors are given in the fixed design model. The conditional normality for a modified version
of the bootstrap wavelet estimators is obtained in the fixed model. The consistency for
the bootstrap wavelet estimator is also proved in the random design model. These results
show that the bootstrap wavelet method is valid for the model with weakly dependent
processes.

Abstract:

Key words: Nonparametric regression;weakly dependent process;bootstrap;wavelet

中图分类号:

林路, 张润楚. BOOTSTRAP WAVELET IN THE NONPARAMETRIC REGRESSION MODEL WITH WEAKLY DEPENDENT PROCESSES[J]. 数学物理学报(英文版), 2004, 24(1): 61-70.

LIN Lu, ZHANG Run-Chu. BOOTSTRAP WAVELET IN THE NONPARAMETRIC REGRESSION MODEL WITH WEAKLY DEPENDENT PROCESSES[J]. Acta mathematica scientia,Series B, 2004, 24(1): 61-70.

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BOOTSTRAP WAVELET IN THE NONPARAMETRIC REGRESSION MODEL WITH WEAKLY DEPENDENT PROCESSES

BOOTSTRAP WAVELET IN THE NONPARAMETRIC REGRESSION MODEL WITH WEAKLY DEPENDENT PROCESSES

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