Title :
Variable bandwidth M-estimators of the partial linear regression models
Author :
Yao, Lili ; Song, Xiangdong
Author_Institution :
Coll. of Sci., Yan Shan Univ., Qinhuangdao, China
Abstract :
In the paper the variable bandwidth M-estimators of the partial linear models are discussed The variable bandwidth M-estimation of the unknown function and local variable bandwidth M-estimators of the unknown parameter is proposed by local linear method. Under the assumptions, the consistence and the asymptotic normality of the estimators of the unknown function and the unknown parameter are proofed. The proposed method inherits the advantages of local polynomial regression and overcomes lack of robustness of least squares techniques.
Keywords :
estimation theory; least squares approximations; regression analysis; asymptotic normality; least squares technique; local linear method; local polynomial regression; partial linear regression model; unknown function; unknown parameter; variable bandwidth M-estimator; Bandwidth; Estimation; Linear regression; Mathematical model; Minimization; Polynomials; Spline; M-estimators; partial linear models; variable bandwidth;
Conference_Titel :
Multimedia Technology (ICMT), 2011 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-61284-771-9
DOI :
10.1109/ICMT.2011.6002638