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Yugoslav Journal of Operations Research
1993, vol. 3, iss. 1, pp. 33-42
article language: English
document type: unclassified
published on: 02/06/2007
Estimating parameters of a multiplicative seasonal ARIMA model using prediction error method algorithm
University of Belgrade, 'Mihajlo Pupin' Institute

Abstract

Estimating the parameters of a model presents only one stage of the time series modeling procedure. This paper describes an effective way of estimating the parameters of the multiplicative seasonal autoregressive integrated moving average (ARIMA) model in a recursive fashion. This 'on line' algorithm is, in contrast to the known 'offline' algorithms noniterative and model independent. The method is based on the Gauss-Newton parameter estimator, updating its gradient and Hessian every time instant some new data becomes available.

Keywords

recursive prediction error algorithm; parameter estimation; multiplicative seasonal ARIMA models

References

Abraham, B., Ledolter, J. (1983) Statistical methods for forecasting. New York, itd: Wiley
Box, G.E.P., Jenkins, G.M. (1976) Time series analysis: Forecasting and control. San Francisco, CA: Holden Day
Ljung, L., Soderstrom, T. (1983) Theory and practice of recursive identification. Cambridge, MA, itd: Massachusetts Institute of Technology Press / MIT Press