AbstractLetX1, …, Xnbe i.i.d. randomd-vectors,d⩾1, with sample meanXand sample covariance matrixS. For testing the hypothesisHdthat the law ofX1is some nondegenerate normal distribution, there is a whole class of practicable affine invariant and universally consistent tests. These procedures are based on weighted integrals of the squared modulus of the difference between the empirical characteristic function of the scaled residualsYj=S−1/2(Xj−X) and its almost sure pointwise limit exp(−‖t‖2/2) underHd. The test statistics have an alternative interpretation in terms ofL2-distances between a nonparametric kernel density estimator and the parametric density estimator underHd, applied toY1, …, Yn. By working in the Fréchet space of continuous f...
AbstractIn this article, we consider the problem of testing that the mean vector μ=0 in the model xj...
Statistical analysis frequently relies on the assumption of normality. Though normality may often be...
Testing the distribution of a random sample can be considered ,indeed, as a goodness-of-fit problem....
AbstractLetX1, …, Xnbe i.i.d. randomd-vectors,d⩾1, with sample meanXand sample covariance matrixS. F...
In this article, we propose a new multiple test procedure for assessing multivariate normality, whic...
We use a system of first-order partial differential equations that characterize the moment generatin...
AbstractWe propose a new class of rotation invariant and consistent goodness-of-fit tests for multiv...
We study a novel class of affine invariant and consistent tests for normality in any dimension in an...
We study a novel class of affine-invariant and consistent tests for multivariate normality. The test...
We generalize a recent class of tests for univariate normality that are based on the empirical momen...
There are a number of methods in the statistical literature for testing whether observed data came f...
AbstractLet X,X1,…,Xm,…, Y,Y1,…,Yn,… be independent d-dimensional random vectors, where the Xj are i...
AbstractThis paper gives a unified treatment of the limit laws of different measures of multivariate...
AbstractIn the class of multivariate exponential power distributions, we derive LBI (locally best in...
AbstractA statistic is proposed for testing the equality of the mean vectors in a one-way multivaria...
AbstractIn this article, we consider the problem of testing that the mean vector μ=0 in the model xj...
Statistical analysis frequently relies on the assumption of normality. Though normality may often be...
Testing the distribution of a random sample can be considered ,indeed, as a goodness-of-fit problem....
AbstractLetX1, …, Xnbe i.i.d. randomd-vectors,d⩾1, with sample meanXand sample covariance matrixS. F...
In this article, we propose a new multiple test procedure for assessing multivariate normality, whic...
We use a system of first-order partial differential equations that characterize the moment generatin...
AbstractWe propose a new class of rotation invariant and consistent goodness-of-fit tests for multiv...
We study a novel class of affine invariant and consistent tests for normality in any dimension in an...
We study a novel class of affine-invariant and consistent tests for multivariate normality. The test...
We generalize a recent class of tests for univariate normality that are based on the empirical momen...
There are a number of methods in the statistical literature for testing whether observed data came f...
AbstractLet X,X1,…,Xm,…, Y,Y1,…,Yn,… be independent d-dimensional random vectors, where the Xj are i...
AbstractThis paper gives a unified treatment of the limit laws of different measures of multivariate...
AbstractIn the class of multivariate exponential power distributions, we derive LBI (locally best in...
AbstractA statistic is proposed for testing the equality of the mean vectors in a one-way multivaria...
AbstractIn this article, we consider the problem of testing that the mean vector μ=0 in the model xj...
Statistical analysis frequently relies on the assumption of normality. Though normality may often be...
Testing the distribution of a random sample can be considered ,indeed, as a goodness-of-fit problem....