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- Publisher
- Springer Journals
- Copyright
- Copyright © 1987 by Science Press, Beijing, China and Allerton Press, Inc. New York, U.S.A.
- Subject
- Mathematics; Applications of Mathematics; Math Applications in Computer Science; Theoretical, Mathematical and Computational Physics
- ISSN
- 0168-9673
- eISSN
- 1618-3932
- DOI
- 10.1007/BF02008373
- Publisher site
- See Article on Publisher Site
Abstract
This paper investigates the generalized least squares estimation and the maximum likelihood estimation of the parameters in a multivariate polychoric correlations model, based on data from a multidimensional contingency table. Asymptotic properties of the estimators are discussed. An iterative procedure based on the Gauss-Newton algorithm is implemented to produce the generalized least squares estimates and the standard errors estimates. It is shown that via an iteratively reweighted method, the algorithm produces the maximum likelihood estimates as well. Numerical results on the finite sample behaviors of the methods are reported.
Journal
Acta Mathematicae Applicatae Sinica – Springer Journals
Published: Jul 13, 2005