<P>具体请见:<a href="http://www.statsnetbase.com/ejournals/books/book_summary/toc.asp?id=636" target="_blank" >http://www.statsnetbase.com/ejournals/books/book_summary/toc.asp?id=636</A>
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<P>Time-Series Forecasting
Chris Chatfield</P>
<P>Summary
From the author of the bestselling "Analysis of Time Series," Time-Series Forecasting offers a comprehensive, up-to-date review of forecasting methods. It provides a summary of time-series modelling procedures, followed by a brief catalogue of many different time-series forecasting methods, ranging from ad-hoc methods through ARIMA and state-space 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 inter-relationships 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 situations-the context is crucial. Time-Series 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.
features
Summarizes the basics of time-series modelling and features a catalogue of forecasting methods
Includes recent arrivals such as GARCH models, neural networks, and cointegrated models
Addresses the computation of prediction intervals and the effect of model uncertainty of forecast accuracy
Offers a self-contained treatment for those with a reasonable, general statistics background
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[此贴子已经被作者于2005-5-7 14:01:57编辑过]