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Consistent Estimation of Order for Regression in the Presence of Serial Correlation and Heteroscedasticity
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作者 CHEN Min 1, WU Guo-fu 1, QI Quan-yue 21.Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Beijing 100080, China2.P.O. Box 1303-15, Beijing 100073, China 《Journal of Systems Science and Systems Engineering》 SCIE EI CSCD 2001年第2期247-256,共10页
In this paper, we consider a multiple regression model in the presence of serial correlation and heteroscedasticity. We establish the convergence rate of an efficient estimation of autoregressive coefficients suggeste... In this paper, we consider a multiple regression model in the presence of serial correlation and heteroscedasticity. We establish the convergence rate of an efficient estimation of autoregressive coefficients suggested by Harvey and Robison (1988). We propose a method to identify order of serial correlation data and prove that it is of strong consistency. The simulation reports show that the method of identifying order is available. 展开更多
关键词 regression serial correlation HETEROSCEDASTICITY two-stage estimation strong consistency convergence rate identification of order of residual autocorrelation
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