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EFFICIENT ESTIMATION OF FUNCTIONAL-COEFFICIENT REGRESSION MODELS WITH DIFFERENT SMOOTHING VARIABLES 被引量:5
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作者 张日权 李国英 《Acta Mathematica Scientia》 SCIE CSCD 2008年第4期989-997,共9页
In this article,a procedure for estimating the coefficient functions on the functional-coefficient regression models with different smoothing variables in different coefficient functions is defined.First step,by the l... In this article,a procedure for estimating the coefficient functions on the functional-coefficient regression models with different smoothing variables in different coefficient functions is defined.First step,by the local linear technique and the averaged method,the initial estimates of the coefficient functions are given.Second step,based on the initial estimates,the efficient estimates of the coefficient functions are proposed by a one-step back-fitting procedure.The efficient estimators share the same asymptotic normalities as the local linear estimators for the functional-coefficient models with a single smoothing variable in different functions.Two simulated examples show that the procedure is effective. 展开更多
关键词 Asymptotic normality averaged method different smoothing variables functional-coefficient regression models local linear method one-step back-fitting procedure
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FUNCTIONAL-COEFFICIENT REGRESSION MODEL AND ITS ESTIMATION 被引量:6
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作者 Mei Changlin Wang NingSchool of Science,Xi’an Jiaotong Univ.,Xi’an 710049. 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 2001年第3期304-314,共11页
In this paper,a class of functional-coefficient regression models is proposed and an estimation procedure based on the locally weighted least equares is suggested.This class of models,with the proposed estimation meth... In this paper,a class of functional-coefficient regression models is proposed and an estimation procedure based on the locally weighted least equares is suggested.This class of models,with the proposed estimation method,is a powerful means for exploratory data analysis. 展开更多
关键词 functional-coefficient regression model locally weighted least equares cross-validation.
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