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IDENTIFICATION OF REGIME SHIFTS IN TIME SERIES USING NEIGHBORHOOD STATISTICS
Citation:
PAWLOWSKI, C. AND H. CABEZAS. IDENTIFICATION OF REGIME SHIFTS IN TIME SERIES USING NEIGHBORHOOD STATISTICS. ECOLOGICAL COMPLEXITY. Elsevier Science, New York, NY, 5(1):30-36, (2008).
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Description:
The identification of alternative dynamic regimes in ecological systems requires several lines of evidence. Previous work on time series analysis of dynamic regimes includes mainly model-fitting methods. We introduce two methods that do not use models. These approaches use state-or measurement-space neighborhood statistics to pick out patterns in time series that are consistent with shifts between alternative dynamic regimes. Analysis of simulated and real data sets shows that these methods can be an effective means of identifying regime shifts for single variable as well as multivariable time series. In addition, these methods can be used on systems with non-equilibrium steady states. However, care must be taken in interpreting results as these methods do respond to changes in time series that are not the result of regime shifts.
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IDENTIFICATION OF REGIME SHIFTS IN TIME SERIES USING NEIGHBORHOOD STATISTICS
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