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Parameter estimation of an autoregressive moving average model

  • Junji Nakano
Article
  • 63 Downloads

Summary

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.

Keywords

Maximum Likelihood Estimator Average Model Circular Condition Prediction Error Variance Scalar Time Series 

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Copyright information

© The Institute of Statistical Mathematics, Tokyo 1982

Authors and Affiliations

  • Junji Nakano
    • 1
  1. 1.Technical College of the University of TokushimaTokushimaJapan

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