Akaike (1974, 1975) has described how canonical variate analysis can be used to identify the structure of linear multivariate time series models. With some modification, the procedure is suitable for finding autoregressive moving average representations which are efficiently parameterized. We describe briefly the method and examine its performance when applied to a well‐known bivariate time series.
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Cooper et al. (1982) studied this question.