IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v51y2006i3p1892-1903.html
   My bibliography  Save this article

Detecting change-points in multidimensional stochastic processes

Author

Listed:
  • De Gooijer, Jan G.

Abstract

No abstract is available for this item.

Suggested Citation

  • De Gooijer, Jan G., 2006. "Detecting change-points in multidimensional stochastic processes," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1892-1903, December.
    • Handle: RePEc:eee:csdana:v:51:y:2006:i:3:p:1892-1903
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(05)00319-1
    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. B. Abraham & W. Wei, 1984. "Inferences about the parameters of a time series model with changing variance," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 31(1), pages 183-194, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bastidon, Cécile & Parent, Antoine & Jensen, Pablo & Abry, Patrice & Borgnat, Pierre, 2020. "Graph-based era segmentation of international financial integration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    2. repec:hal:spmain:info:hdl:2441/ps168627s85g86i5u1aj5akpm is not listed on IDEAS
    3. Bastidon, Cécile & Parent, Antoine & Jensen, Pablo & Abry, Patrice & Borgnat, Pierre, 2020. "Graph-based era segmentation of international financial integration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    4. Cheon, Sooyoung & Kim, Jaehee, 2010. "Multiple change-point detection of multivariate mean vectors with the Bayesian approach," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 406-415, February.
    5. Pedro Galeano & Dominik Wied, 2017. "Dating multiple change points in the correlation matrix," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(2), pages 331-352, June.
    6. David Hallac & Peter Nystrup & Stephen Boyd, 2019. "Greedy Gaussian segmentation of multivariate time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(3), pages 727-751, September.
    7. Galeano, Pedro & Wied, Dominik, 2014. "Multiple break detection in the correlation structure of random variables," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 262-282.

    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. Xu, Ke-Li & Phillips, Peter C.B., 2008. "Adaptive estimation of autoregressive models with time-varying variances," Journal of Econometrics, Elsevier, vol. 142(1), pages 265-280, January.
    2. Galeano, Pedro, 2004. "Variance changes detection in multivariate time series," DES - Working Papers. Statistics and Econometrics. WS ws041305, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Baisuo Jin & Mong-Na Lo Huang & Baiqi Miao, 2011. "Testing for variance changes in autoregressive models with unknown order," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(5), pages 927-936, January.
    4. Wenzhi Zhao & Zheng Tian & Zhiming Xia, 2010. "Ratio test for variance change point in linear process with long memory," Statistical Papers, Springer, vol. 51(2), pages 397-407, June.

    More about this item

    Statistics

    Access and download statistics

    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:csdana:v:51:y:2006:i:3:p:1892-1903. 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/locate/csda .

    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.