A UNIFIED APPROACH TO ARMA MODEL IDENTIFICATION AND PRELIMINARY ESTIMATION

D. Piccolo and G. Tunnicliffe Wilson

Journal of Time Series Analysis, 1984, vol. 5, issue 3, 183-204

Abstract: Abstract. This paper reviews several different methods for identifying the orders of autoregressive‐moving average models for time series data. The case is made that these have a common basis, and that a unified approach may be found in the analysis of a matrix G, defined to be the covariance matrix of forecast values. The estimation of this matrix is considered, emphasis being placed on the use of high order autoregression to approximate the predictor coefficients. Statistical procedures are proposed for analysing G, and identifying the model orders. A simulation example and three sets of real data are used to illustrate the procedure, which appears to be a very useful tool for order identification and preliminary model estimation.

Date: 1984
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Persistent link: https://EconPapers.repec.org/RePEc:bla:jtsera:v:5:y:1984:i:3:p:183-204

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