Fitting a Linear Autoregressive Model for Long-Range Forecasting

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  • 1 Department of Meteorology, Nanjing University, people's Republic of China
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Abstract

Methods of fitting a linear autoregressive model to a stationary time series are summarized. Parameters of the linear autoregressive model were estimated by the Durbin stepwise procedure and the order of this model was chosen by means of a t-test or F-test. An illustrative example used to forecast the monthly rainfall is also presented.

Abstract

Methods of fitting a linear autoregressive model to a stationary time series are summarized. Parameters of the linear autoregressive model were estimated by the Durbin stepwise procedure and the order of this model was chosen by means of a t-test or F-test. An illustrative example used to forecast the monthly rainfall is also presented.

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