IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v5y1987i4p337-356.html
   My bibliography  Save this article

Correspondence analysis with least absolute residuals

Author

Listed:
  • Heiser, Willem J.

Abstract

No abstract is available for this item.

Suggested Citation

  • Heiser, Willem J., 1987. "Correspondence analysis with least absolute residuals," Computational Statistics & Data Analysis, Elsevier, vol. 5(4), pages 337-356, September.
    • Handle: RePEc:eee:csdana:v:5:y:1987:i:4:p:337-356
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0167-9473(87)90057-0
    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.

    Citations

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


    Cited by:

    1. Willem Heiser, 1991. "A generalized majorization method for least souares multidimensional scaling of pseudodistances that may be negative," Psychometrika, Springer;The Psychometric Society, vol. 56(1), pages 7-27, March.
    2. Choulakian, V., 2001. "Robust Q-mode principal component analysis in L1," Computational Statistics & Data Analysis, Elsevier, vol. 37(2), pages 135-150, August.
    3. de Leeuw, Jan & Lange, Kenneth, 2009. "Sharp quadratic majorization in one dimension," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2471-2484, May.
    4. Michailidis, George & De Leeuw, Jan, 2005. "Homogeneity analysis using absolute deviations," Computational Statistics & Data Analysis, Elsevier, vol. 48(3), pages 587-603, March.
    5. Choulakian, Vartan, 2005. "Transposition invariant principal component analysis in L1 for long tailed data," Statistics & Probability Letters, Elsevier, vol. 71(1), pages 23-31, January.
    6. Choulakian, V., 2006. "L1-norm projection pursuit principal component analysis," Computational Statistics & Data Analysis, Elsevier, vol. 50(6), pages 1441-1451, March.
    7. Ke-Hai Yuan & Peter Bentler, 2000. "Robust mean and covariance structure analysis through iteratively reweighted least squares," Psychometrika, Springer;The Psychometric Society, vol. 65(1), pages 43-58, March.
    8. Ehtibar Dzhafarov & Hans Colonius, 2006. "Reconstructing Distances among Objects from Their Discriminability," Psychometrika, Springer;The Psychometric Society, vol. 71(2), pages 365-386, June.
    9. Groenen, P.J.F. & Giaquinto, P. & Kiers, H.A.L., 2003. "Weighted Majorization Algorithms for Weighted Least Squares Decomposition Models," Econometric Institute Research Papers EI 2003-09, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    10. Henk Kiers & Patrick Groenen, 1996. "A monotonically convergent algorithm for orthogonal congruence rotation," Psychometrika, Springer;The Psychometric Society, vol. 61(2), pages 375-389, June.
    11. Henk Kiers, 1997. "Weighted least squares fitting using ordinary least squares algorithms," Psychometrika, Springer;The Psychometric Society, vol. 62(2), pages 251-266, June.
    12. Peter Verboon & Ivo Lans, 1994. "Robust canonical discriminant analysis," Psychometrika, Springer;The Psychometric Society, vol. 59(4), pages 485-507, December.
    13. Henk Kiers, 1990. "Majorization as a tool for optimizing a class of matrix functions," Psychometrika, Springer;The Psychometric Society, vol. 55(3), pages 417-428, September.
    14. Jacqueline Meulman, 1992. "The integration of multidimensional scaling and multivariate analysis with optimal transformations," Psychometrika, Springer;The Psychometric Society, vol. 57(4), pages 539-565, December.
    15. Shizuhiko Nishisato, 1996. "Gleaning in the field of dual scaling," Psychometrika, Springer;The Psychometric Society, vol. 61(4), pages 559-599, December.

    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:5:y:1987:i:4:p:337-356. 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: 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.