A CLASS OF DISTRIBUTION-FREE TESTS FOR INDEPENDENCE AGAINST POSITIVE QUADRANT DEPENDENCE

A Class of Distribution-free Tests for Independence against Positive Quadrant Dependence

A class of distribution-free tests based on convex combination of two U-statistics is considered for testing independence against positive quadrant dependence. The class of tests proposed by Kochar and Gupta (1987) and Kendall’s test are members of the proposed class. The performance of the proposed class is evaluated in terms of Pitman asymptotic relative efficiency for BlockBasu (1974) model ...

A class of multivariate distribution-free tests of independence based on graphs.

A class of distribution-free tests is proposed for the independence of two subsets of response coordinates. The tests are based on the pairwise distances across subjects within each subset of the response. A complete graph is induced by each subset of response coordinates, with the sample points as nodes and the pairwise distances as the edge weights. The proposed test statistic depends only on...

A new class of independence tests for interval forecasts evaluation

Interval forecasts evaluation can be reduced to examining the unconditional coverage and independence properties of the hit sequence. A new class of exact independence tests for the hit sequence and a definition for tendency to clustering of violations are proposed. The tests are suitable for detecting models with a tendency to generate clusters of violations and are based on an exact distribut...

I - 1 a Class of Permutation Tests for Stochastic Independence

On the Permutation Distribution of Independence Tests

One of the most popular class of tests for independence between two random variables is the general class of rank statistics which are invariant under permutations. This class contains Spearman’s coefficient of rank correlation statistic, Fisher-Yates statistic, weighted Mann statistic and others. Under the null hypothesis of independence these test statistics have a permutation distribution th...