Applying the strong approximation technique we present a unified approach to asymptotic results for multivariate linear rank statistics for the two-sample problem. We reprove asymptotic normality of these statistics under the null hypothesis and under local alternatives convergent at a moderate rate to the null hypothesis. We also provide a moderate deviation theorem for these statistics under the null hypothesis. Proofs are short and use natural argumentation.Applying the strong approximation technique we present a unified approach to asymptotic results for multivariate linear rank statistics for the two-sample problem. We reprove asymptotic normality of these statistics under the null hypothesis and under local alternatives converge...
Rank statistics to test the null hypothesis that $ X $ and $ Y $ are conditionally, given $ Z $, ind...
Asymptotic linearity plays a key role in estimation and testing in the presence of nuisance paramete...
This thesis deals with univariate and multivariate rank methods in making statistical inference. It ...
Asymptotic multinormality of linear rank statistics based on independent vector valued random variab...
The joint asymptotic multinormality of certain linear signed-rank statistics introduced by Shane and...
AbstractThe joint asymptotic multinormality of certain linear signed-rank statistics introduced by S...
AbstractA new approach to the asymptotic normality of the multivariate linear rank statistics is pro...
summary:The equivalence of the symmetry of density of the distribution of observations and the oddne...
When a statistic with a complicated distribution is dealt, the asymptotic distribution is often used...
By modifying the method of projection, the results of Hajek and Huskova are extended to show the asy...
The purpose of the paper is to extend the weak asymptotic results for the weighted partial sums of i...
summary:Let $X_j, 1\leq j\leq N$, be independent random $p$-vectors with respective continuous cumul...
summary:The purpose of the paper is to investigate weak asymptotic behaviour of rank statistics prop...
AbstractBy modifying the method of projection, the results of Hajek and Huskova are extended to show...
Typescript (photocopy).In this dissertation, weak convergence results for dependent sequences are us...
Rank statistics to test the null hypothesis that $ X $ and $ Y $ are conditionally, given $ Z $, ind...
Asymptotic linearity plays a key role in estimation and testing in the presence of nuisance paramete...
This thesis deals with univariate and multivariate rank methods in making statistical inference. It ...
Asymptotic multinormality of linear rank statistics based on independent vector valued random variab...
The joint asymptotic multinormality of certain linear signed-rank statistics introduced by Shane and...
AbstractThe joint asymptotic multinormality of certain linear signed-rank statistics introduced by S...
AbstractA new approach to the asymptotic normality of the multivariate linear rank statistics is pro...
summary:The equivalence of the symmetry of density of the distribution of observations and the oddne...
When a statistic with a complicated distribution is dealt, the asymptotic distribution is often used...
By modifying the method of projection, the results of Hajek and Huskova are extended to show the asy...
The purpose of the paper is to extend the weak asymptotic results for the weighted partial sums of i...
summary:Let $X_j, 1\leq j\leq N$, be independent random $p$-vectors with respective continuous cumul...
summary:The purpose of the paper is to investigate weak asymptotic behaviour of rank statistics prop...
AbstractBy modifying the method of projection, the results of Hajek and Huskova are extended to show...
Typescript (photocopy).In this dissertation, weak convergence results for dependent sequences are us...
Rank statistics to test the null hypothesis that $ X $ and $ Y $ are conditionally, given $ Z $, ind...
Asymptotic linearity plays a key role in estimation and testing in the presence of nuisance paramete...
This thesis deals with univariate and multivariate rank methods in making statistical inference. It ...