Wavelet-Based Estimators of the Mean Regression Function With Long Memory Date

LI Lin-yuan; XIAO Yi-min

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LI Lin-yuan, XIAO Yi-min. Wavelet-Based Estimators of the Mean Regression Function With Long Memory Date[J]. Applied Mathematics and Mechanics, 2006, 27(7): 789-798.

Citation:

LI Lin-yuan, XIAO Yi-min. Wavelet-Based Estimators of the Mean Regression Function With Long Memory Date[J]. Applied Mathematics and Mechanics, 2006, 27(7): 789-798.

Citation:

LI Lin-yuan, XIAO Yi-min. Wavelet-Based Estimators of the Mean Regression Function With Long Memory Date[J]. Applied Mathematics and Mechanics, 2006, 27(7): 789-798.

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Wavelet-Based Estimators of the Mean Regression Function With Long Memory Date

LI Lin-yuan¹,
XIAO Yi-min²

1.
Department of Mathematics and Statistics, University of New Hampshire, USA;

Received Date: 2005-01-17
Rev Recd Date: 2006-04-09
Publish Date: 2006-07-15

Abstract

Abstract

An asymptotic expansion is provide for the mean integrated squared error (MISE) of nonlinear wavelet-based mean regression function estimators with long memory data. This MISE expansion is shown, when the underlying mean regression function is only piecewise smooth. It is the same with analogous expansion for the kernel estimators. However, for the kernel estimators, this MISE expansion generally fails if the additional smoothness assumption is absent.
- mean integrated square error,
- nonparametric regression,
- nonlinear wavelet-based estimator,
- rate of convergence

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References(25)

References

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