Title :
The Approximate Distribution of Nonparametric Regression Estimates
Author_Institution :
Coll. of Math. & Comput. Sci., Guangxi Univ. for Nat., Nanning, China
Abstract :
An improved normal approximation is obtained for the joint distribution of kernel nonparametric regression estimates, in the presence of arbitrarily many stochastic regressors and heteroscedastic but conditionally normal errors. The approximation and its goodness are affected by kernel choice and bandwidth rate.
Keywords :
Bandwidth; Computer errors; Computer science; Distributed computing; Educational institutions; Kernel; Least squares approximation; Mathematics; Stochastic processes; Sufficient conditions; kernel estimates; nonparametric regression; optimal bandwidth; stochastic regressors;
Conference_Titel :
Computational Science and Optimization (CSO), 2010 Third International Joint Conference on
Conference_Location :
Huangshan, Anhui, China
Print_ISBN :
978-1-4244-6812-6
Electronic_ISBN :
978-1-4244-6813-3
DOI :
10.1109/CSO.2010.172
