Kalman filter estimation for periodic autoregressive-moving average models |
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| Authors: | C Jimenez A I McLeod K W Hipel |
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| Institution: | (1) Dept. of Statistical and Actuarial Sciences, University of Western Ontario, N6A 5B9 London, Ontario, Canada;(2) Dept. of Systems Design Engineering and Dept. of Statistics and Actuarial Sciences, University of Waterloo, N2L 3G1 Waterloo, Ontario, Canada |
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| Abstract: | An exact maximum likelihood procedure is presented for estimating the parameters of a periodic autogressive-moving average (PARMA) model. To develop an estimator which is both statistically and computationally efficient, the PARMA class of models is written using a state-space representation and a Kalman filtering algorithm is used to estimate the parameters. In order to demonstrate how to fit PARMA models in practice, the most appropriate types of PARMA models are identified for fitting to two average monthly riverflow time series and the new estimator is employed for estimating the model parameters. |
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| Keywords: | Kalman filter Maximum likelihood estimation Periodic models Stochastic hydrology Time series analysis |
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