The application of Taylor expansion to error density estimation nonparametric regression

Qingjian Zeng; Qing Li

doi:10.1117/12.954151

8 June 2012 The application of Taylor expansion to error density estimation nonparametric regression

Qingjian Zeng, Qing Li

Proceedings Volume 8334, Fourth International Conference on Digital Image Processing (ICDIP 2012); 833423 (2012) https://doi.org/10.1117/12.954151
Event: Fourth International Conference on Digital Image Processing (ICDIP 2012), 2012, Kuala Lumpur, Malaysia

Abstract

In this paper, by applying the Taylor expansion, the authors study the asymptotic properties of the kernel density estimation f_n(e) of an unknown error distribution function f(e) in a nonparametric regression model. Then, they study the choice of the smoothing parameters in the estimation f_n(e). Finally, an approximation confidence interval of f(e) was given.

Citation Download Citation

Qingjian Zeng and Qing Li "The application of Taylor expansion to error density estimation nonparametric regression", Proc. SPIE 8334, Fourth International Conference on Digital Image Processing (ICDIP 2012), 833423 (8 June 2012); https://doi.org/10.1117/12.954151

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