IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v76y2006i12p1201-1210.html
   My bibliography  Save this article

Asymptotic fluctuations of mutagrams

Author

Listed:
  • Müller, Hans-Georg
  • Wai, Newton

Abstract

Abrupt changes in sequential data, known as change-points, can be detected by fitting differences of one-sided kernel estimators. The detection depends on both a bandwidth and a threshold, where we declare a change-point whenever the differences of the one-sided kernel estimators exceed the threshold. The joint behavior of the difference of one-sided kernel estimators and scale can be graphically represented in a mutagram [Müller, H.G., Wai, N., 2004. Change trees and mutagrams for the visualization of local changes in sequence data. J. Comput. Statist. Graph. 13, 571-585.]. Here we study the fluctuations of the mutagram values in dependency on different bandwidth choices, corresponding to scale. Study of these fluctuations is related to the SiZer approach of Chaudhuri and Marron [2000. Scale space view of curve estimation. Ann. Statist. 28, 408-428.]. We explore the asymptotic properties and convergence of a local bandwidth process for differences of one-sided kernel estimators. These processes are shown to be tight with a Gaussian limit process that represents the asymptotic fluctuations of mutagrams. These fluctuations are illustrated with a sequence of vertical ocean shear data.

Suggested Citation

  • Müller, Hans-Georg & Wai, Newton, 2006. "Asymptotic fluctuations of mutagrams," Statistics & Probability Letters, Elsevier, vol. 76(12), pages 1201-1210, July.
  • Handle: RePEc:eee:stapro:v:76:y:2006:i:12:p:1201-1210
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-7152(05)00476-1
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Irene Gijbels & Peter Hall & Aloïs Kneip, 1999. "On the Estimation of Jump Points in Smooth Curves," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 51(2), pages 231-251, June.
    2. Lee, Chung-Bow, 1996. "Nonparametric multiple change-point estimators," Statistics & Probability Letters, Elsevier, vol. 27(4), pages 295-304, May.
    3. Grégoire, Gérard & Hamrouni, Zouhir, 2002. "Change Point Estimation by Local Linear Smoothing," Journal of Multivariate Analysis, Elsevier, vol. 83(1), pages 56-83, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Porter, Jack & Yu, Ping, 2015. "Regression discontinuity designs with unknown discontinuity points: Testing and estimation," Journal of Econometrics, Elsevier, vol. 189(1), pages 132-147.
    2. Huh, Jib, 2010. "Detection of a change point based on local-likelihood," Journal of Multivariate Analysis, Elsevier, vol. 101(7), pages 1681-1700, August.
    3. Einmahl, J.H.J. & Gantner, M., 2009. "The Half-Half Plot," Other publications TiSEM 88c03da5-f408-4cd8-a7f9-0, Tilburg University, School of Economics and Management.
    4. Daniel J. Henderson & Christopher F. Parmeter & Liangjun Su, 2017. "M-Estimation of a Nonparametric Threshold Regression Model," Working Papers 2017-15, University of Miami, Department of Economics.
    5. Gantner, M., 2010. "Some nonparametric diagnostic statistical procedures and their asymptotic behavior," Other publications TiSEM eb04bdba-bf8a-4f6c-8dd8-9, Tilburg University, School of Economics and Management.
    6. Yicheng Kang & Xiaodong Gong & Jiti Gao & Peihua Qiu, 2016. "Error-in-Variables Jump Regression Using Local Clustering," Monash Econometrics and Business Statistics Working Papers 13/16, Monash University, Department of Econometrics and Business Statistics.
    7. Grégoire, Gérard & Hamrouni, Zouhir, 2002. "Change Point Estimation by Local Linear Smoothing," Journal of Multivariate Analysis, Elsevier, vol. 83(1), pages 56-83, October.
    8. Zhanfeng Wang & Wenxin Liu & Yuanyuan Lin, 2015. "A change-point problem in relative error-based regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(4), pages 835-856, December.
    9. Irène Gijbels & Alexandre Lambert & Peihua Qiu, 2007. "Jump-Preserving Regression and Smoothing using Local Linear Fitting: A Compromise," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 59(2), pages 235-272, June.
    10. Cui, Yan & Yang, Jun & Zhou, Zhou, 2023. "State-domain change point detection for nonlinear time series regression," Journal of Econometrics, Elsevier, vol. 234(1), pages 3-27.
    11. Xiaodong Gong & Jiti Gao, 2015. "Nonparametric Kernel Estimation of the Impact of Tax Policy on the Demand for Private Health Insurance in Australia," Monash Econometrics and Business Statistics Working Papers 6/15, Monash University, Department of Econometrics and Business Statistics.
    12. Moosup Kim & Sangyeol Lee, 2011. "Change point test for tail index for dependent data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 74(3), pages 297-311, November.
    13. Genest Christian & Scherer Matthias, 2023. "When copulas and smoothing met: An interview with Irène Gijbels," Dependence Modeling, De Gruyter, vol. 11(1), pages 1-16, January.
    14. Lingsong Zhang & Zhengyuan Zhu & J. S. Marron, 2014. "Multiresolution anomaly detection method for fractional Gaussian noise," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(4), pages 769-784, April.
    15. Davis, Richard A. & Hancock, Stacey A. & Yao, Yi-Ching, 2016. "On consistency of minimum description length model selection for piecewise autoregressions," Journal of Econometrics, Elsevier, vol. 194(2), pages 360-368.
    16. Pan, Jianmin & Chen, Jiahua, 2006. "Application of modified information criterion to multiple change point problems," Journal of Multivariate Analysis, Elsevier, vol. 97(10), pages 2221-2241, November.
    17. Kohler, Michael & Krzyżak, Adam, 2015. "Estimation of a jump point in random design regression," Statistics & Probability Letters, Elsevier, vol. 106(C), pages 247-255.
    18. Lin, Zhengyan & Li, Degui & Chen, Jia, 2008. "Change point estimators by local polynomial fits under a dependence assumption," Journal of Multivariate Analysis, Elsevier, vol. 99(10), pages 2339-2355, November.
    19. Nora M. Villanueva & Marta Sestelo & Miguel M. Fonseca & Javier Roca-Pardiñas, 2023. "seq2R: An R Package to Detect Change Points in DNA Sequences," Mathematics, MDPI, vol. 11(10), pages 1-20, May.
    20. I. Sánchez-Borrego & M. Martínez-Miranda & A. González-Carmona, 2006. "Local linear kernel estimation of the discontinuous regression function," Computational Statistics, Springer, vol. 21(3), pages 557-569, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:stapro:v:76:y:2006:i:12:p:1201-1210. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.