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Sequential Analysis
Design Methods and Applications
Volume 35, 2016 - Issue 3
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DISCUSSION 5

Discussion on “Sequential detection/isolation of abrupt changes” by Igor V. Nikiforov

Pages 320-323 | Received 01 Apr 2016, Accepted 28 May 2016, Published online: 16 Sep 2016

References

  • Fellouris, G. and Tartakovsky, A. G. (2016). Multichannel Sequential Detection—Part I: Non-i.i.d. Data, IEEE Transactions on Information Theory (to be published).
  • Mei, Y. (2010). Efficient Scalable Schemes for Monitoring a Large Number of Data Streams, Biometrika 97: 419–433.
  • Nikiforov, I. V. (1995). A Generalized Change Detection Problem, IEEE Transactions on Information Theory 41: 171–187.
  • Pollak, M. and Tartakovsky, A. G. (2009). Asymptotic Exponentiality of the Distribution of First Exit Times for a Class of Markov Processes with Applications to Quickest Change Detection, Theory of Probability and Its Applications 53: 430–442.
  • Siegmund, D. (2013). Change-Points: From Sequential Detection to Biology and Back, Sequential Analysis 32: 2–14.
  • Tartakovsky, A. G. (2013). Discussion on “Change-Points: From Sequential Detection to Biology and Back” by David Siegmund, Sequential Analysis 32: 36–42.
  • Tartakovsky, A. G., Nikiforov, I. V., and Basseville, M. (2014). Sequential Analysis: Hypothesis Testing and Changepoint Detection, Boca Raton: Chapman & Hall/CRC Press.
  • Xie, Y. and Siegmund, D. (2013). Sequential Multi-Sensor Change-Point Detection, Annals of Statistics 41: 670–692.
  • Yakir, B. (1995). A Note on the Run Length to False Alarm of a Change-Point Detection Policy, Annals of Statistics 23: 272–281.

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