IDEAS home Printed from https://ideas.repec.org/a/bes/jnlasa/v106i495y2011p1009-1024.html
   My bibliography  Save this article

Independent Component Analysis Involving Autocorrelated Sources With an Application to Functional Magnetic Resonance Imaging

Author

Listed:
  • Lee, Seonjoo
  • Shen, Haipeng
  • Truong, Young
  • Lewis, Mechelle
  • Huang, Xuemei

Abstract

No abstract is available for this item.

Suggested Citation

  • Lee, Seonjoo & Shen, Haipeng & Truong, Young & Lewis, Mechelle & Huang, Xuemei, 2011. "Independent Component Analysis Involving Autocorrelated Sources With an Application to Functional Magnetic Resonance Imaging," Journal of the American Statistical Association, American Statistical Association, vol. 106(495), pages 1009-1024.
    • Handle: RePEc:bes:jnlasa:v:106:i:495:y:2011:p:1009-1024
    as

    Download full text from publisher

    File URL: http://pubs.amstat.org/doi/abs/10.1198/jasa.2011.tm10332
    File Function: full text
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    Citations

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


    Cited by:

    1. Chen, Ray-Bing & Chen, Ying & Härdle, Wolfgang K., 2014. "TVICA—Time varying independent component analysis and its application to financial data," Computational Statistics & Data Analysis, Elsevier, vol. 74(C), pages 95-109.
    2. Chen, Ying & Niu, Linlin & Chen, Ray-Bing & He, Qiang, 2019. "Sparse-Group Independent Component Analysis with application to yield curves prediction," Computational Statistics & Data Analysis, Elsevier, vol. 133(C), pages 76-89.
    3. Lee, Seonjoo & Shen, Haipeng & Truong, Young, 2021. "Sampling properties of color Independent Component Analysis," Journal of Multivariate Analysis, Elsevier, vol. 181(C).
    4. Jari Miettinen & Katrin Illner & Klaus Nordhausen & Hannu Oja & Sara Taskinen & Fabian J. Theis, 2016. "Separation of Uncorrelated Stationary time series using Autocovariance Matrices," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(3), pages 337-354, May.
    5. Geoffrey Colin L. Peterson & Dong Li & Brian J. Reich & Donald Brenner, 2017. "Spatial prediction of crystalline defects observed in molecular dynamic simulations of plastic damage," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(10), pages 1761-1784, July.
    6. Marijke Welvaert & Yves Rosseel, 2013. "On the Definition of Signal-To-Noise Ratio and Contrast-To-Noise Ratio for fMRI Data," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-10, November.

    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:bes:jnlasa:v:106:i:495:y:2011:p:1009-1024. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Christopher F. Baum (email available below). General contact details of provider: http://www.amstat.org/publications/jasa/index.cfm?fuseaction=main .

    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.