AbstractIn 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
There is a lot of interest in positive dependence going beyond linear correlation. In this paper thr...
Characterization problems of setwise independence are considered by introducing the setwise dependen...
AbstractThe concepts of conditionally more positively quadrant dependent, and conditionally more dis...
AbstractIn this paper, the set of all bivariate positive quadrant dependent distributions with fixed...
The set of all bivariate probability distributions with support contained in {(i,j); I=1, 2 and J = ...
A new class of tests based on convex combination of the two statistics is proposed. These are func...
AbstractThe set of all bivariate probability distributions with support contained in {(i,j); i=1, 2 ...
We consider distributional free inference to test for positive quadrant dependence, that is, for the...
We consider distributional free inference to test for positive quadrant dependence, i.e. for the pro...
A class of distribution-free tests based on convex combination of two U-statistics is considered for...
An exact conditional approach is developed to test for certain forms of positive association betwee...
A class of distribution-free tests based on convex combination of two U-statistics is considered for...
We develop an empirical likelihood (EL) approach to test independence of two univariate random varia...
AbstractCharacterization problems of setwise independence are considered by introducing the setwise ...
AbstractThe geometry of the set of p × q probability mass function matrices with fixed marginals is ...
There is a lot of interest in positive dependence going beyond linear correlation. In this paper thr...
Characterization problems of setwise independence are considered by introducing the setwise dependen...
AbstractThe concepts of conditionally more positively quadrant dependent, and conditionally more dis...
AbstractIn this paper, the set of all bivariate positive quadrant dependent distributions with fixed...
The set of all bivariate probability distributions with support contained in {(i,j); I=1, 2 and J = ...
A new class of tests based on convex combination of the two statistics is proposed. These are func...
AbstractThe set of all bivariate probability distributions with support contained in {(i,j); i=1, 2 ...
We consider distributional free inference to test for positive quadrant dependence, that is, for the...
We consider distributional free inference to test for positive quadrant dependence, i.e. for the pro...
A class of distribution-free tests based on convex combination of two U-statistics is considered for...
An exact conditional approach is developed to test for certain forms of positive association betwee...
A class of distribution-free tests based on convex combination of two U-statistics is considered for...
We develop an empirical likelihood (EL) approach to test independence of two univariate random varia...
AbstractCharacterization problems of setwise independence are considered by introducing the setwise ...
AbstractThe geometry of the set of p × q probability mass function matrices with fixed marginals is ...
There is a lot of interest in positive dependence going beyond linear correlation. In this paper thr...
Characterization problems of setwise independence are considered by introducing the setwise dependen...
AbstractThe concepts of conditionally more positively quadrant dependent, and conditionally more dis...