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From the author of the bestselling 'Analysis of Time Series,' TimeSeries Forecasting offers a comprehensive, uptodate review of forecasting methods. It provides a summary of timeseries modelling procedures, followed by a brief catalogue of many different timeseries forecasting methods, ranging from adhoc methods through ARIMA and statespace modelling to multivariate methods and including recent arrivals, such as GARCH models, neural networks, and cointegrated models.The author compares the more important methods in terms of their theoretical interrelationships and their practical merits. He also considers two other general forecasting topics that have been somewhat neglected in the literature: the computation of prediction intervals and the effect of model uncertainty on forecast accuracy.Although the search for a 'best' method continues, it is now well established that no single method will outperform all other methods in all situationsthe context is crucial. TimeSeries Forecasting provides an outstanding reference source for the more generally applicable methods particularly useful to researchers and practitioners in forecasting in the areas of economics, government, industry, and commerce.
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