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Nonlinear wavelet smoothing of error distribution in a semi-parametric model

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Author Info
Z. Li
G. Chai
K.Xu

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Abstract

Consider a semiparametric model yi = xi' beta + g(ti )+ei; i = 1;2..., n, error ei are i.i.d. random variables from unknown distribution f(e). In this paper, we propose a nonlinear wavelet estimator ^f(e) of f(e) based on residuals ê =yi - ^yi here restriction of uniformly continuous on f(e) might beavoided. Following the way used in Hall et al (1995), we provide an asymptotic formula for the mean integrated squared error of ^ f(e), some numerical examples will be given in the end of the paper.

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Publisher Info
Paper provided by University of Bonn, Germany in its series Discussion Paper Serie A with number 567.

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Date of creation: Dec 1997
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Handle: RePEc:bon:bonsfa:567

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Postal: Bonn Graduate School of Economics, University of Bonn, Adenauerallee 24 - 26, 53113 Bonn, Germany
Fax: +49 228 73 9221
Web page: http://www.bgse.uni-bonn.de/index.php?id=517

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Related research
Keywords: wavelet; semiparametric model; nonlinear wavelet estimator; income distribution;

Find related papers by JEL classification:
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution

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This page was last updated on 2009-11-15.

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