AbstractBased upon the idea of construction of data driven smooth tests for composite hypotheses presented in Inglotet al.(1997) and Kallenberg and Ledwina (1997), two versions of data driven smooth test for bivariate normality are proposed. Asymptotic null distributions are derived, and consistency of the newly introduced tests against every bivariate alternative with marginals having finite variances is proved. Included results of power simulations show that one of the proposed tests performs very well in comparison with other commonly used tests for bivariate normality
AbstractWe propose a new class of rotation invariant and consistent goodness-of-fit tests for multiv...
There are three methods, which are most commonly used to assess the bivariate normality of paired da...
Abstract. Goodness-of-fit tests based on sums of squared com-ponents or the Cramir-von Mises statist...
AbstractBased upon the idea of construction of data driven smooth tests for composite hypotheses pre...
In many statistical studies the relationship between two random variables X and Y is investigated an...
Rao's score statistic is a standard tool for constructing statistical tests.If departures from the n...
In recent years several authors have recommended smooth tests for testing goodness of fit. However, ...
In recent years several authors have recommended smooth tests for testing goodness of fit. However, ...
The data driven method of selecting the number of components in Neyman's smooth test for uniformity,...
This paper considers the problem of testing the equality of two unspecified distributions. The class...
A test of multivariate normality given by Koziol (1986, 1987) is examined in some detail for the biv...
Smooth tests of goodness of fit assess the fit of data to a given probability density function withi...
Statistical analysis frequently relies on the assumption of normality. Though normality may often be...
New data-driven smooth tests are proposed in this thesis. The new testsre proposed to eschew the dow...
In this paper, we propose a test for bivariate normality in imperfectly observed models, based on th...
AbstractWe propose a new class of rotation invariant and consistent goodness-of-fit tests for multiv...
There are three methods, which are most commonly used to assess the bivariate normality of paired da...
Abstract. Goodness-of-fit tests based on sums of squared com-ponents or the Cramir-von Mises statist...
AbstractBased upon the idea of construction of data driven smooth tests for composite hypotheses pre...
In many statistical studies the relationship between two random variables X and Y is investigated an...
Rao's score statistic is a standard tool for constructing statistical tests.If departures from the n...
In recent years several authors have recommended smooth tests for testing goodness of fit. However, ...
In recent years several authors have recommended smooth tests for testing goodness of fit. However, ...
The data driven method of selecting the number of components in Neyman's smooth test for uniformity,...
This paper considers the problem of testing the equality of two unspecified distributions. The class...
A test of multivariate normality given by Koziol (1986, 1987) is examined in some detail for the biv...
Smooth tests of goodness of fit assess the fit of data to a given probability density function withi...
Statistical analysis frequently relies on the assumption of normality. Though normality may often be...
New data-driven smooth tests are proposed in this thesis. The new testsre proposed to eschew the dow...
In this paper, we propose a test for bivariate normality in imperfectly observed models, based on th...
AbstractWe propose a new class of rotation invariant and consistent goodness-of-fit tests for multiv...
There are three methods, which are most commonly used to assess the bivariate normality of paired da...
Abstract. Goodness-of-fit tests based on sums of squared com-ponents or the Cramir-von Mises statist...