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Parameter Estimation of Varying Coefficients Structural EV Model with Time Series 被引量:1

Parameter Estimation of Varying Coefficients Structural EV Model with Time Series
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摘要 In this paper, the parameters of a p-dimensional linear structural EV(error-in-variable)model are estimated when the coefficients vary with a real variable and the model error is time series.The adjust weighted least squares(AWLS) method is used to estimate the parameters. It is shown that the estimators are weakly consistent and asymptotically normal, and the optimal convergence rate is also obtained. Simulations study are undertaken to illustrate our AWLSEs have good performance. In this paper, the parameters of a p-dimensional linear structural EV(error-in-variable)model are estimated when the coefficients vary with a real variable and the model error is time series.The adjust weighted least squares(AWLS) method is used to estimate the parameters. It is shown that the estimators are weakly consistent and asymptotically normal, and the optimal convergence rate is also obtained. Simulations study are undertaken to illustrate our AWLSEs have good performance.
出处 《Acta Mathematica Sinica,English Series》 SCIE CSCD 2017年第5期607-619,共13页 数学学报(英文版)
基金 Supported by the Educational Commission of Hubei Province of China(Grant No.D20112503) National Natural Science Foundation of China(Grant Nos.11071022,11231010 and 11028103) the foundation of Beijing Center of Mathematics and Information Sciences
关键词 Varying coefficient EV model adjust weighted least squares estimators linear stationary time series CONSISTENCY asymptotic normality Varying coefficient EV model adjust weighted least squares estimators linear stationary time series consistency asymptotic normality
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