Optimal estimation for doubly multivariate data in blocked compound symmetric covariance structure

Anuradha Roy, Roman Zmyślony (), Miguel Fonseca and Ricardo Leiva
Additional contact information
Anuradha Roy: UTSA

Working Papers from College of Business, University of Texas at San Antonio

Abstract: The paper deals with the best unbiased estimators of the blocked compound symmetric covariance structure for m??variate observations over u sites under the assumption of multivariate normality. The free-coordinate approach is used to prove that the quadratic estimation of covariance parameters is equivalent to linear estimation with a properly defined inner product in the space of symmetric matrices. Complete statistics are then derived to prove that the estimators are best unbiased. Finally, strong consistency is proven. The proposed method is implemented with a real data set.

Keywords: Best unbiased estimator; blocked compound symmetric covariance structure; doubly multivariate data; coordinate free approach (search for similar items in EconPapers)
JEL-codes: C13 (search for similar items in EconPapers)
Pages: 17 pages
Date: 2015
References: Add references at CitEc
Citations:

Published in Review of Economics, March 1999, pages 1-23

Downloads: (external link)
http://interim.business.utsa.edu/wps/mss/0006MSS-253-2015.pdf Full text (application/pdf)
Our link check indicates that this URL is bad, the error code is: 404 Not Found

Related works:
Journal Article: Optimal estimation for doubly multivariate data in blocked compound symmetric covariance structure (2016)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:tsa:wpaper:0165mss

Access Statistics for this paper

More papers in Working Papers from College of Business, University of Texas at San Antonio Contact information at EDIRC.
Bibliographic data for series maintained by Wendy Frost ().