8 June 2012 The application of Taylor expansion to error density estimation nonparametric regression
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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 fn(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 fn(e). Finally, an approximation confidence interval of f(e) was given.
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Qingjian Zeng, Qingjian Zeng, Qing Li, 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); doi: 10.1117/12.954151; https://doi.org/10.1117/12.954151
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