Parameter estimation of an autoregressive moving average model
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An estimator of the set of parameters of an autoregressive moving average model is obtained by applying the method of least squares to the log smoothed periodogram. It is shown to be asymptotically efficient and normally distributed under the normality and the circular condition of the generating process. A computational procedure is constructed by the Newton-Raphson method. Several computer simulation results are given to demonstrate the usefulness of the present procedure.
KeywordsMaximum Likelihood Estimator Average Model Circular Condition Prediction Error Variance Scalar Time Series
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- Clevenson, M. L. (1970). Asymptotically efficient estimates of the parameters of a moving average time series, Ph.D. Dissertation, Department of Statistics, Stanford University.Google Scholar