AbstractMultivariate generalizations of Bhuchongkul's bivariate rank statistics [Ann. Math. Statist.35 (1964)] have been introduced and studied in this paper for the purpose of testing mulitvariate independence. It is shown that the test statistics can be expressed as rank statistics which are easy to compute, have asymptotic normal distributions, and can detect mutual dependence in alternatives which are pairwise independent. The tests are compared to the Puri-Sen-Gokhale [Sankyha Ser. A32 (1970)] tests and a normal theory test [Anderson, “An Introduction to Statistical Analysis,” Wiley, 1958] using Pitman efficiency
AbstractA nonparametric test of the mutual independence between many numerical random vectors is pro...
International audienceA nonparametric test of the mutual independence between many numerical random ...
The problem of testing the hypothesis of independence against multiparametrical set of alternatives ...
AbstractMultivariate generalizations of Bhuchongkul's bivariate rank statistics [Ann. Math. Statist....
The problem of testing mutual independence of p random vectors in a general setting where the dimens...
Thesis (Ph.D.)--University of Washington, 2021Testing independence is a fundamental statistical prob...
New test statistics are proposed for testing whether two random vectors are independent. Gieser and ...
The nonparametrie tests of bivariate independence, based on Spearman's rho, Kendall's tau, the Blum-...
AbstractA new nonparametric approach to the problem of testing the joint independence of two or more...
New rank scores test statistics are proposed for testing whether two random vectors are independent....
A class of nonparametric tests based on the third quad-rant layer ranks has recently been studied by...
Intraclass rank statistics are introduced to test for independence in a bivariate population when it...
The detection of dependence structures within a set of random variables provides a valuable basis fo...
Three simple and explicit procedures for testing the independence of two multi-dimensional random va...
In testing independence of two random variables based on rank statistics, several rank statistics su...
AbstractA nonparametric test of the mutual independence between many numerical random vectors is pro...
International audienceA nonparametric test of the mutual independence between many numerical random ...
The problem of testing the hypothesis of independence against multiparametrical set of alternatives ...
AbstractMultivariate generalizations of Bhuchongkul's bivariate rank statistics [Ann. Math. Statist....
The problem of testing mutual independence of p random vectors in a general setting where the dimens...
Thesis (Ph.D.)--University of Washington, 2021Testing independence is a fundamental statistical prob...
New test statistics are proposed for testing whether two random vectors are independent. Gieser and ...
The nonparametrie tests of bivariate independence, based on Spearman's rho, Kendall's tau, the Blum-...
AbstractA new nonparametric approach to the problem of testing the joint independence of two or more...
New rank scores test statistics are proposed for testing whether two random vectors are independent....
A class of nonparametric tests based on the third quad-rant layer ranks has recently been studied by...
Intraclass rank statistics are introduced to test for independence in a bivariate population when it...
The detection of dependence structures within a set of random variables provides a valuable basis fo...
Three simple and explicit procedures for testing the independence of two multi-dimensional random va...
In testing independence of two random variables based on rank statistics, several rank statistics su...
AbstractA nonparametric test of the mutual independence between many numerical random vectors is pro...
International audienceA nonparametric test of the mutual independence between many numerical random ...
The problem of testing the hypothesis of independence against multiparametrical set of alternatives ...