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Time Series Regression Models

Part of the Springer Texts in Statistics book series (STS)

In this chapter, we introduce several useful ideas that incorporate external information into time series modeling. We start with models that include the effects of interventions on time series’ normal behavior. We also consider models that assimilate the effects of outliers—observations, either in the observed series or in the error terms, that are highly unusual relative to normal behavior. Lastly, we develop methods to look for and deal with spurious correlation—correlation between series that is artificial and will not help model or understand the time series of interest. We will see that prewhitening of series helps us find meaningful relationships.

Keywords

Time Series Ordinary Little Square Spurious Correlation Gasoline Price Time Series Plot 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2008

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