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A General Asymptotic Theory for Time Series Models
Shiqing, Ling
96960
McAleer, Michael
96961
335
Asymptotic normality
estimation
rate of strong convergence
strong consistency
time series models
application/pdf
This paper develops a general asymptotic theory for the estimation of strictly stationary and ergodic time series models. Under simple conditions that are straightforward to check, we establish the strong consistency, the rate of strong convergence and the asymptotic normality of a general class of estimators that includes LSE, MLE, and some M-type estimators. As an application, we verify the assumptions for the long-memory fractional ARIMA model. Other examples include the GARCH(1,1) model, random coefficient AR(1) model and the threshold MA(1) model.
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technical report
日本経済国際共同センター
2009-09
Discussion paper series. CIRJE-F
CIRJE-F-670
AA11450569
eng
http://www.cirje.e.u-tokyo.ac.jp/research/dp/2009/2009cf670ab.html
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