IDEAS home Printed from https://ideas.repec.org/p/lau/crdeep/9616.html
   My bibliography  Save this paper

Prediction and Sufficiency in the Model of Factor Analysis

Author

Listed:
  • Ramses H. ABUL NAGA

Abstract

We contrast two approaches to the prediction of latent variables in the model of factor analysis. The likelihood statistic constitutes the set of minimal sufficient statistics for the unobservables when sampling arises from the exponential family of distributions. Linear predictors on the other hand can be obtained as distribution-free statistics. The paper provides conditions under which a class of linear predictors is sufficient for the exponential family of distributions.

Suggested Citation

  • Ramses H. ABUL NAGA, 1996. "Prediction and Sufficiency in the Model of Factor Analysis," Cahiers de Recherches Economiques du Département d'Econométrie et d'Economie politique (DEEP) 9616, Université de Lausanne, Faculté des HEC, DEEP.
  • Handle: RePEc:lau:crdeep:9616
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Riccardo Massari, 2005. "A Measure of Welfare Based on Permanent Income Hypothesis: An Application on Italian Households Budgets," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 64(1), pages 55-92, September.

    More about this item

    Keywords

    latent variables; factor analysis; sufficiency; prediction; exponential familiy of distributions; living standards analysis;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • I30 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General

    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:lau:crdeep:9616. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Gaëlle Sarda). General contact details of provider: http://edirc.repec.org/data/deelsch.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.