Abstract
The determination of an appropriate ARMA(p, q) model to represent an observed stationary time series involves a number of inter-related problems. These include the choice of p and q (order selection), and estimation of the remaining parameters, i.e. the mean, the coefficients {φ i , θ j : i = 1,..., p; j = 1,..., q} and the white noise variance σ 2, for given values of p and q. Goodness of fit of the model must also be checked and the estimation procedure repeated with different values of p and q. Final selection of the most appropriate model depends on a variety of goodness of fit tests, although it can be systematized to a large degree by use of criteria such as the AICC statistic discussed in Chapter 9.
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© 1991 Springer Science+Business Media New York
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Brockwell, P.J., Davis, R.A. (1991). Estimation for ARMA Models. In: Time Series: Theory and Methods. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0320-4_8
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DOI: https://doi.org/10.1007/978-1-4419-0320-4_8
Publisher Name: Springer, New York, NY
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