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Distinguishing diffusive and jumpy behaviors in real-world time series

Rahimi Tabar, M. R ; Sharif University of Technology | 2019

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  1. Type of Document: Article
  2. DOI: 10.1007/978-3-030-18472-8_19
  3. Publisher: Springer Verlag , 2019
  4. Abstract:
  5. Jumps are discontinuous variations in time series and with large amplitude can be considered as an extreme event. We expect the higher the jump activity to cause higher uncertainty in the stochastic behaviour of measured time series. Therefore, building statistical evidence to detect real jump seems of primary importance. In addition jump events can participate in the observed non-Gaussian feature of the increments’ (ramp up and ramp down) statistics of many time series [1]. This is the reason that most of the jump detection techniques are based on threshold values for differential of time series. There is not, however, a robust method for detection and characterisation of such discontinuous events that is able to estimate time-dependence of the “jump rate” and their amplitudes, etc. © 2019, Springer Nature Switzerland AG
  6. Keywords:
  7. Abrupt transitions ; Distinguishing diffusive from jumpy stochastic behaviors ; Stationary and nonstationary time series
  8. Source: Understanding Complex Systems ; 2019 , Pages 207-213 ; 18600832 (ISSN)
  9. URL: https://link.springer.com/chapter/10.1007%2F978-3-030-18472-8_19