Add to ORKGIn this paper there is given a new approach for testing hypotheses on the structure of covariance matrices in double multivariate data. It is proved that ratio of positive and negative parts of best unbiased estimators (BUE) provide an F-test for independence of blocks variables in double multivariate models
summary:In regular multivariate regression model a test of linear hypothesis is dependent on a struc...
This thesis concerns inference problems in balanced random effects models with a so-called block cir...
We develop methods to compare multiple multivariate normally distributed samples which may be correl...
The stability of covariance matrix is a major issue in multivariate analysis. As can be seen in the ...
The stability of covariance matrix is a major issue in multivariate analysis. As can be seen in the ...
In this paper we proposed a new statistical test for testing the covariance matrix in one population...
AbstractWe consider two hypothesis testing problems with N independent observations on a single m-ve...
AbstractThis paper considers three types of problems: (i) the problem of independence of two sets, (...
The focus in this thesis is on the calculations of an empirical null distributionfor likelihood rati...
We consider the general family of multivariate normal distributions where the mean vector lies in an...
Likelihood ratio tests are derived for testing the structure of mean values in a two-way classificat...
In this article we develop a test statistic for testing the equality of mean vectors for paired doub...
In this article, we address the problem of simultaneous testing hypothesis about mean and covariance...
AbstractThe classical problem of testing the equality of the covariance matrices from k⩾2 p-dimensio...
AbstractThe null hypothesis that the error vectors in a multivariate linear model are independent is...
summary:In regular multivariate regression model a test of linear hypothesis is dependent on a struc...
This thesis concerns inference problems in balanced random effects models with a so-called block cir...
We develop methods to compare multiple multivariate normally distributed samples which may be correl...
The stability of covariance matrix is a major issue in multivariate analysis. As can be seen in the ...
The stability of covariance matrix is a major issue in multivariate analysis. As can be seen in the ...
In this paper we proposed a new statistical test for testing the covariance matrix in one population...
AbstractWe consider two hypothesis testing problems with N independent observations on a single m-ve...
AbstractThis paper considers three types of problems: (i) the problem of independence of two sets, (...
The focus in this thesis is on the calculations of an empirical null distributionfor likelihood rati...
We consider the general family of multivariate normal distributions where the mean vector lies in an...
Likelihood ratio tests are derived for testing the structure of mean values in a two-way classificat...
In this article we develop a test statistic for testing the equality of mean vectors for paired doub...
In this article, we address the problem of simultaneous testing hypothesis about mean and covariance...
AbstractThe classical problem of testing the equality of the covariance matrices from k⩾2 p-dimensio...
AbstractThe null hypothesis that the error vectors in a multivariate linear model are independent is...
summary:In regular multivariate regression model a test of linear hypothesis is dependent on a struc...
This thesis concerns inference problems in balanced random effects models with a so-called block cir...
We develop methods to compare multiple multivariate normally distributed samples which may be correl...