Add to ORKGIntraclass rank statistics are introduced to test for independence in a bivariate population when it has the same continuous marginal distributions. Locally most powerful intraclass rank tests (LMPIRT) are derived for a oneparameter family and asymptotic normality of a family of intraclass rank statistics including LMPIRT is shown under the hypothesis of independence and its contiguous alternatives. Furthermore, approximations of the null distributions of the statistics are discussed
New rank scores test statistics are proposed for testing whether two random vectors are independent....
AbstractA nonparametric test of the mutual independence between many numerical random vectors is pro...
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...
The problem of testing the hypothesis of independence against multiparametrical set of alternatives ...
AbstractMultivariate generalizations of Bhuchongkul's bivariate rank statistics [Ann. Math. Statist....
A class of nonparametric tests based on the third quad-rant layer ranks has recently been studied by...
Rank correlations have found many innovative applications in the last decade. In particular,suitable...
In this paper, a class of nonparametric tests for independence between two continuous random variabl...
We propose a new class of nonparametric tests for the supposition of independence between two contin...
Thesis (Ph.D.)--University of Washington, 2021Testing independence is a fundamental statistical prob...
Blest (2000, Aust. N. Z. J. Stat. 42, 101-111) proposed a new measure of rank correlation that is se...
The nonparametrie tests of bivariate independence, based on Spearman's rho, Kendall's tau, the Blum-...
In nonparametric tests for serial independence the marginal distribution of the data acts as an infi...
International audienceA nonparametric test of the mutual independence between many numerical random ...
New rank scores test statistics are proposed for testing whether two random vectors are independent....
AbstractA nonparametric test of the mutual independence between many numerical random vectors is pro...
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...
The problem of testing the hypothesis of independence against multiparametrical set of alternatives ...
AbstractMultivariate generalizations of Bhuchongkul's bivariate rank statistics [Ann. Math. Statist....
A class of nonparametric tests based on the third quad-rant layer ranks has recently been studied by...
Rank correlations have found many innovative applications in the last decade. In particular,suitable...
In this paper, a class of nonparametric tests for independence between two continuous random variabl...
We propose a new class of nonparametric tests for the supposition of independence between two contin...
Thesis (Ph.D.)--University of Washington, 2021Testing independence is a fundamental statistical prob...
Blest (2000, Aust. N. Z. J. Stat. 42, 101-111) proposed a new measure of rank correlation that is se...
The nonparametrie tests of bivariate independence, based on Spearman's rho, Kendall's tau, the Blum-...
In nonparametric tests for serial independence the marginal distribution of the data acts as an infi...
International audienceA nonparametric test of the mutual independence between many numerical random ...
New rank scores test statistics are proposed for testing whether two random vectors are independent....
AbstractA nonparametric test of the mutual independence between many numerical random vectors is pro...
Three simple and explicit procedures for testing the independence of two multi-dimensional random va...