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This introduction presents forecasting methods and models for time series analysis, highlighting key techniques.
Simple descriptive techniques probability models for time series estimation in the time domain forecasting stationary processes in the frequency domain spectral analysis bivariate processes linear systems state-space models and the Kalman filter non-linear models multivariate time series modelling some other topics.
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Dickey et al. (1991) studied this question.
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