IDEAS home Printed from https://ideas.repec.org/a/bla/jorssc/v40y1991i1p159-170.html
   My bibliography  Save this article

Reduced Rank Models with Two Sets of Regressors

Author

Listed:
  • Raja P. Velu

Abstract

Interest has been growing in the use and extensions of multivariate reduced rank regression procedures in applied research and data modelling. This paper considers an extension of the model proposed by Anderson. Asymptotic theory and an iterative computational procedure for the relevant estimators of the extended model are briefly discussed. to illustrate these methods, ozone data collected in Europe are considered.

Suggested Citation

  • Raja P. Velu, 1991. "Reduced Rank Models with Two Sets of Regressors," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 40(1), pages 159-170, March.
  • Handle: RePEc:bla:jorssc:v:40:y:1991:i:1:p:159-170
    DOI: 10.2307/2347914
    as

    Download full text from publisher

    File URL: https://doi.org/10.2307/2347914
    Download Restriction: no

    File URL: https://libkey.io/10.2307/2347914?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

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


    Cited by:

    1. Pietro Lovaglio, 2011. "Model building and estimation strategies for implementing the Balanced Scorecard in Health sector," Quality & Quantity: International Journal of Methodology, Springer, vol. 45(1), pages 199-212, January.
    2. Wayne DeSarbo & Heungsun Hwang & Ashley Stadler Blank & Eelco Kappe, 2015. "Constrained Stochastic Extended Redundancy Analysis," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 516-534, June.
    3. Yoshio Takane & Henk Kiers & Jan Leeuw, 1995. "Component analysis with different sets of constraints on different dimensions," Psychometrika, Springer;The Psychometric Society, vol. 60(2), pages 259-280, June.
    4. Geweke, John, 1996. "Bayesian reduced rank regression in econometrics," Journal of Econometrics, Elsevier, vol. 75(1), pages 121-146, November.
    5. Takane, Yoshio & Hwang, Heungsun, 2005. "An extended redundancy analysis and its applications to two practical examples," Computational Statistics & Data Analysis, Elsevier, vol. 49(3), pages 785-808, June.
    6. Yoshio Takane & Sunho Jung, 2008. "Regularized Partial and/or Constrained Redundancy Analysis," Psychometrika, Springer;The Psychometric Society, vol. 73(4), pages 671-690, 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:bla:jorssc:v:40:y:1991:i:1:p:159-170. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    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.