This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Information-Theoretic Distribution Test With Application to Normality

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Stengos, T.
Wu, X.

Additional information is available for the following registered author(s):

Abstract

No abstract is available for this item.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help file. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.economics.uoguelph.ca/Research/DisPapers/2006_4.pdf
File Format:
File Function:
Download Restriction: no

Publisher Info
Paper provided by University of Guelph, Department of Economics in its series Working Papers with number 2006-4.

Download reference. The following formats are available: HTML, plain text, BibTeX, RIS (EndNote), ReDIF
Length: 23 pages
Date of creation: 2006
Date of revision:
Handle: RePEc:gue:guelph:2006-4

Contact details of provider:
Postal: Guelph, Ontario, N1G 2W1
Phone: (519) 824-4120 ext. 53898
Fax: (519) 763-8497
Web page: http://www.economics.uoguelph.ca/index.htm
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: (Anton Miglo).

Related research
Keywords:

Other versions of this item:

This paper has been announced in the following NEP Reports: References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Bontemps, Christian & Meddahi, Nour, 2005. "Testing normality: a GMM approach," Journal of Econometrics, Elsevier, vol. 124(1), pages 149-186, January. [Downloadable!] (restricted)
  2. D. Ormoneit & H. White, 1999. "An efficient algorithm to compute maximum entropy densities," Econometric Reviews, Taylor and Francis Journals, vol. 18(2), pages 127-140. [Downloadable!] (restricted)
  3. Zellner, Arnold & Highfield, Richard A., 1988. "Calculation of maximum entropy distributions and approximation of marginalposterior distributions," Journal of Econometrics, Elsevier, vol. 37(2), pages 195-209, February. [Downloadable!] (restricted)
  4. Thanasis Stengos & Ximing Wu, 2005. "Partially Adaptive Estimation via Maximum Entropy Densities," University of Cyprus Working Papers in Economics 7-2005, University of Cyprus Department of Economics. [Downloadable!]
  5. Ximing Wu & Thanasis Stengos, 2005. "Partially adaptive estimation via the maximum entropy densities," Econometrics Journal, Royal Economic Society, vol. 8(3), pages 352-366, December. [Downloadable!] (restricted)
  6. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January. [Downloadable!] (restricted)
  7. Guido W. Imbens & Richard H. Spady & Phillip Johnson, 1998. "Information Theoretic Approaches to Inference in Moment Condition Models," Econometrica, Econometric Society, vol. 66(2), pages 333-358, March.
    Other versions:
Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Ekrem Kilic, 2005. "A Nonparametric Way of Distribution Testing," Econometrics 0510006, EconWPA. [Downloadable!]
Statistics
Access and download statistics

Did you know? About 2000 working paper series are listed on RePEc.

This page was last updated on 2008-7-25.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.