Skip to main content
Log in

Comments on: Extensions of some classical methods in change point analysis

  • Discussion
  • Published:
TEST Aims and scope Submit manuscript

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

References

  • Ciuperca G (2013) Two tests for sequential detection of a change-point in a nonlinear model. J Stat Plann Infer 143:1719–1743

    Article  MATH  MathSciNet  Google Scholar 

  • Doukhan P, Kegne W (2013) Inference and testing for structural change in time series of counts model. arXiv:1305.1751

  • Fokianos K (2012) Count time series models. In: Rao CR, Subba Rao T (eds) Handbook in statistics. Time series-methods and applications, vol 30. Elsevier B.V, Amsterdam, pp 315–348

    Chapter  Google Scholar 

  • Fokianos K, Gombay E, Hussein A (2014) Retrospective change detection for binary time series models. J Stat Plann Infer 145:102–112

  • Franke J, Kirch C, Tadjuidje Kamgaing J (2012) Changepoints in times series of counts. J Time Ser Anal 33:757–770

    Article  MATH  MathSciNet  Google Scholar 

  • Hlávka Z, Hušková M, Kirch C, Meintanis S (2012) Monitoring changes in the error distribution of autoregressive models based on fourier methods. Test 21:605–634

    Article  MATH  MathSciNet  Google Scholar 

  • Hlávka Z, Hušková M, Kirch C, Meintanis S (2014) Bootstrap procedures for on-line monitoring of changes in autoregressive models. Commun Stat Simulation Comput

  • Hudecová S (2013) Structural changes in autoregressive models for binary time series. J Stat Plann Inf 143(10):1744–1752

    Article  MATH  Google Scholar 

  • Hušková M (2004) Permutation principle and bootstrap in change point analysis. Fields Inst Commun 44:273–291

    Google Scholar 

  • Hušková M, Hlávka Z (2012) Nonparametric sequential monitoring. Seq Anal 31(3):278–296

    MATH  Google Scholar 

  • Hušková M, Kirch C (2008) Bootstrapping confidence intervals for the change-point of time series. J Time Ser Anal 29:947–972

    Article  MATH  MathSciNet  Google Scholar 

  • Hušková M, Kirch C (2010) A note on studentized confidence intervals in change-point analysis. Comput Stat 25:269–289

    Article  MATH  Google Scholar 

  • Hušková M, Kirch C (2012) Bootstrapping sequential change-point tests for linear regression. Metrika 75:673–708

    Article  MATH  MathSciNet  Google Scholar 

  • Hušková M, Meintanis S (2006) Change point analysis based on empirical characteristic functions. Metrika 63(2):145–168

    Article  MATH  MathSciNet  Google Scholar 

  • Kirch C (2007) Block permutation principles for the change analysis of dependent data. J Stat Plann Infer 137:2453–2474

    Article  MATH  MathSciNet  Google Scholar 

  • Kirch C (2008) Bootstrapping sequential change-point tests. Seq Anal 27:330–349

    Article  MATH  MathSciNet  Google Scholar 

  • Kirch C, Politis DN (2011) Tft-bootstrap: resampling time series in the frequency domain to obtain replicates in the time domain. Ann Stat 39:1427–1470

    Article  MATH  MathSciNet  Google Scholar 

  • Kirch C, Tadjuidje Kamgaing J (2014) Monitoring time series based on estimating functions. University of Kaiserslautern

  • Kirch C, Tajduidje Kamgaing J (2014) Detection of change points in discrete valued time series. In: Handbook of discrete valued time series. In: Davis RA, Holan SA, Lund RB, Ravishanker N

  • Weiss CH (2011) Detecting mean increases in poisson inar(1) processes with ewma control charts. J Appl Stat 38:383–398

    Article  MathSciNet  Google Scholar 

  • Weiß CH, Testik MC (2011) The poisson inar(1) cusum chart under overdispersion and estimation error. IIE Trans 43(11):805–818

  • Yontay P, Weiß CH, Testik MC, Bayindir ZP (2012) A two-sided cumulative sum chart for first-order integer-valued autoregressive processes of poisson counts. Qual Reliab Eng Int 29:33–42

    Article  Google Scholar 

Download references

Acknowledgments

The position of the author was financed by the Stifterverband für die deutsche Wissenschaft by funds of the Claussen-Simon-trust.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Claudia Kirch.

Additional information

This comment refers to the invited paper available at: doi:10.1007/s11749-014-0368-4.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kirch, C. Comments on: Extensions of some classical methods in change point analysis. TEST 23, 270–275 (2014). https://doi.org/10.1007/s11749-014-0377-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11749-014-0377-3

Keywords

Navigation