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Testing Serial Correlation in Semiparametric Varying-Coefficient Partially Linear EV Models

Testing Serial Correlation in Semiparametric Varying-Coefficient Partially Linear EV Models
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摘要 This paper studies estimation and serial correlation test of a semiparametric varying-coefficient partially linear EV model of the form Y = X^Tβ +Z^Tα(T) +ε,ξ = X + η with the identifying condition E[(ε,η^T)^T] =0, Cov[(ε,η^T)^T] = σ^2Ip+1. The estimators of interested regression parameters /3 , and the model error variance σ2, as well as the nonparametric components α(T), are constructed. Under some regular conditions, we show that the estimators of the unknown vector β and the unknown parameter σ2 are strongly consistent and asymptotically normal and that the estimator of α(T) achieves the optimal strong convergence rate of the usual nonparametric regression. Based on these estimators and asymptotic properties, we propose the VN,p test statistic and empirical log-likelihood ratio statistic for testing serial correlation in the model. The proposed statistics are shown to have asymptotic normal or chi-square distributions under the null hypothesis of no serial correlation. Some simulation studies are conducted to illustrate the finite sample performance of the proposed tests. This paper studies estimation and serial correlation test of a semiparametric varying-coefficient partially linear EV model of the form Y = X^Tβ +Z^Tα(T) +ε,ξ = X + η with the identifying condition E[(ε,η^T)^T] =0, Cov[(ε,η^T)^T] = σ^2Ip+1. The estimators of interested regression parameters /3 , and the model error variance σ2, as well as the nonparametric components α(T), are constructed. Under some regular conditions, we show that the estimators of the unknown vector β and the unknown parameter σ2 are strongly consistent and asymptotically normal and that the estimator of α(T) achieves the optimal strong convergence rate of the usual nonparametric regression. Based on these estimators and asymptotic properties, we propose the VN,p test statistic and empirical log-likelihood ratio statistic for testing serial correlation in the model. The proposed statistics are shown to have asymptotic normal or chi-square distributions under the null hypothesis of no serial correlation. Some simulation studies are conducted to illustrate the finite sample performance of the proposed tests.
出处 《Acta Mathematicae Applicatae Sinica》 SCIE CSCD 2008年第1期99-116,共18页 应用数学学报(英文版)
基金 Supported by the National Natural Science Foundation of China (No.40574003) the National Natural Science of Hunan (NO.03JJY3065).
关键词 Varying-coefficient model partial linear EV model the generalized least squares estimation serial correlation empirical likelihood Varying-coefficient model, partial linear EV model, the generalized least squares estimation, serial correlation, empirical likelihood
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  • 4王启华.经验似然统计推断方法发展综述[J].数学进展,2004,33(2):141-151. 被引量:24

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