A structure theorem on bivariate positive quadrant dependent distributions and tests for independence in two-way contingency tables
In this paper, the set of all bivariate positive quadrant dependent distributions with fixed marginals is shown to be compact and convex. Extreme points of this convex set are enumerated in some specific examples. Applications are given in testing the hypothesis of independence against strict positive quadrant dependence in the context of ordinal contingency tables. The performance of two tests, one of which is based on eigenvalues of a random matrix, is compared. Various procedures based upon certain functions of the eigenvalues of a random matrix are also proposed for testing for independence in a two-way contingency table when the marginals are random.
Year of publication: |
1987
|
---|---|
Authors: | Rao, M. Bhaskara ; Krishnaiah, P.R. ; Subramanyam, K. |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 23.1987, 1, p. 93-118
|
Publisher: |
Elsevier |
Keywords: | asymptotic distributions compact set contingency tables convex set eigenvalues extreme points gamma ratio hypothesis of independence positive quadrant dependent distributions power function |
Saved in:
Saved in favorites
Similar items by person
-
Analysis of odds ratios in 2 - n ordinal contingency tables
Subramanyam, K., (1988)
-
The structure of some classes of bivariate distributions and some applications
Bhaskara Rao, M., (1990)
-
THIRD ORDER EFFICIENCY OF THE MAXIMUM LIKELIHOOD ESTIMATOR IN THE MULTINOMIAL DISTRIBUTION
Rao, C. R., (1982)
- More ...