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Application of the Surrogate Test to Detect Dynamic Non-Linearity in Ground-Level Ozone Time-Series from Berlin

  • Uwe Schlink
  • Peggy Haase

Abstract

Recent applications of non-parametric methods to forecast ground level ozone concentrations are based on dynamic non-linearity of the data series. We explain the surrogate method to test this assumption, illustrate the method with non-linear data generated by the Lorenz system, and discuss our test results for Berlin ozone time-series. We find that the null-hypothesis of linearity is clearly rejected for 12- and 24-step-ahead predictions of hourly ozone concentrations.

Keywords

Prediction Accuracy Ozone Concentration Atmospheric Environment Query Point Lorenz System 
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-Verlag Wien 2001

Authors and Affiliations

  • Uwe Schlink
  • Peggy Haase
    • 1
  1. 1.Department of Human Exposure Research and EpidemiologyUFZ-Centre for Environmental Research Leipzig-HalleLeipzigGermany

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