Time Series Forecasting by ARARMA Models.
TEXAS A AND M UNIV COLLEGE STATION INST OF STATISTICS
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The relation between various basic problems of time series analysis is presented. Exponential smoothing methods are developed from the point of view prediction theory and extended. ARARMA models are introduced. Methods of ARARMA model fitting are outlined. Since the proof of the pudding is in the eating, the methods proposed are illustrated using some classic examples of time series, including international airline passengers, Makridakis metals series and sunspots.
- Statistics and Probability