IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v8y1995i4p267-81.html
   My bibliography  Save this article

Tensor Methods of Full-Information Maximum Likelihood Estimation: Estimation with Parameter Constraints

Author

Listed:
  • Greenblatt, Seth A

Abstract

In this study, we take a method presented in an earlier paper, called a tensor method, and apply it to the computation of constrained FIML estimates. This technique is based upon a fourth order approximation to the log-likelihood function, rather than the second order approximation used in standard methods. The higher order terms are low rank third and fourth order tensors that are computed, at very little storage or computation cost, using information from previous iterations. We discuss interior and exterior point methods for constrained optimization, show how they can be used in conjunction with tensor methods, and then present test results showing that the tensor method is far more efficient than the standard Newton's method for a wide range of constrained FIML estimation problems. Citation Copyright 1995 by Kluwer Academic Publishers.

Suggested Citation

  • Greenblatt, Seth A, 1995. "Tensor Methods of Full-Information Maximum Likelihood Estimation: Estimation with Parameter Constraints," Computational Economics, Springer;Society for Computational Economics, vol. 8(4), pages 267-281, November.
    • Handle: RePEc:kap:compec:v:8:y:1995:i:4:p:267-81
    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.

    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:kap:compec:v:8:y:1995:i:4:p:267-81. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.