Estimation of the Semiparametric Additive Model with First Order Autoregressive Errors
Estimation of the semiparametric additive time series model with first order autoregressive errors is mainly studied.We suppose that the regression function has a parametric framework,and through the local L2-fitting criterion,parametric vector estimators and semiparametric estimators of the regression function can be given under the use of nonparametric kernel function method.Furthermore,under certain regular conditions,the consistency of the estimators is proved.Finally,simulation research and empirical analysis are presented to evaluate the effectiveness and feasibility of the proposed method.
semiparametric additive time series modelsfirst order autoregressive errorslocal L2-fitting criterionkernel function adjustment
万方数据
维普
