Detecting shocks : Outliers and breaks in time series

  title={Detecting shocks : Outliers and breaks in time series},
  • Published 2003
A single outlier in a regression model can be detected by the effect of its deletion on the residual s irn of squares. An equivalent procedure is the simple intervention in which an extra parameter is added for the mean of the observation in question. Similarly, for unobserved components or structural time-series models, the effect of elaborations of the model on inferences can be investigated by the use of interventions involving a single parameter, such as trend or level changes. Because such… CONTINUE READING


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