**Research partially supported by OnR contract N00014-80-C-0741. ApprW for p e r Afja&MW The current status, including small-sample behavior and ease of computa-tion, of rank-based estimates and tests in the general linear model is reviewed. For the important special case of Wilcoxon scores, details of application of various procedures are discussed. The three different testing methods considered may each be motivated by connecting it to one of three forms of the usual least-squares F statistic. Possible algorithms for computation of rank-based estimates and tests are presented. Each procedure is applied to an example using data. Finally, the technical assumptions made to obtain large-sample properties of these procedures, including the...
Linear models with stable error densities are considered, and their local asymptotic normality with ...
Linear models in which the unobserved error constitutes a realization of some stationary ARMA proces...
We propose a novel statistic to test the rank of a matrix. The rank statistic overcomes deficiencies...
The rank and regression rank score tests of linear hypothesis in the linear regression model are mod...
and Jaeckel proposed rank estimation for linear models. Since that time, several authors have develo...
Testing and estimating the rank of a matrix of estimated parameters is key in a large variety of eco...
summary:In this paper a new rank test in a linear regression model is introduced. The test statistic...
The thesis deals with R-estimators, estimators based on ranks. They were originally proposed by Hodg...
In order to obtain exact distributional results without imposing restrictive parametric assumptions,...
The rank-based method is a well-known robust estimation technique in analyzing linear models, it ser...
This paper develops an approach to rank testing that nests all existing rank tests and simplifies th...
For some general multivariate linear models, linear rank statistics are used in conjunction with Roy...
This paper considers tests for the rank of a matrix for which a root-T consistent estimator is avail...
summary:In the development of efficient predictive models, the key is to identify suitable predictor...
There has recently been renewed research interest in the development of tests of the rank of a matri...
Linear models with stable error densities are considered, and their local asymptotic normality with ...
Linear models in which the unobserved error constitutes a realization of some stationary ARMA proces...
We propose a novel statistic to test the rank of a matrix. The rank statistic overcomes deficiencies...
The rank and regression rank score tests of linear hypothesis in the linear regression model are mod...
and Jaeckel proposed rank estimation for linear models. Since that time, several authors have develo...
Testing and estimating the rank of a matrix of estimated parameters is key in a large variety of eco...
summary:In this paper a new rank test in a linear regression model is introduced. The test statistic...
The thesis deals with R-estimators, estimators based on ranks. They were originally proposed by Hodg...
In order to obtain exact distributional results without imposing restrictive parametric assumptions,...
The rank-based method is a well-known robust estimation technique in analyzing linear models, it ser...
This paper develops an approach to rank testing that nests all existing rank tests and simplifies th...
For some general multivariate linear models, linear rank statistics are used in conjunction with Roy...
This paper considers tests for the rank of a matrix for which a root-T consistent estimator is avail...
summary:In the development of efficient predictive models, the key is to identify suitable predictor...
There has recently been renewed research interest in the development of tests of the rank of a matri...
Linear models with stable error densities are considered, and their local asymptotic normality with ...
Linear models in which the unobserved error constitutes a realization of some stationary ARMA proces...
We propose a novel statistic to test the rank of a matrix. The rank statistic overcomes deficiencies...