In this article we obtain a superexponential rate of convergence in total variation between the traces first m powers n×n random unitary matrices and 2m-dimensional Gaussian variable. This generalizes previous results scalar case to multivariate setting, also give precise dependence on dimensions n estimates with explicit constants. We are especially interested regime where grows our main resul...

It is well-known that the skew-normal distribution can provide an alternative model to the normal distribution for analyzing asymmetric data. The aim of this paper is to propose two goodness-of-fit tests for assessing whether a sample comes from a multivariate skew-normal (MSN) distribution. We address the problem of multivariate skew-normality goodness-of-fit based on the empirical Laplace tra...

Let X1;X2;...;Xn have a jointly multivariate exchangeable normal distribution. In this work we investigate another proof of the independence of X and S2 using order statistics. We also assume that (Xi ; Yi); i =1; 2;...; n; jointly distributed in bivariate normal and establish the independence of the mean and the variance of concomitants of order statistics.

probabilistic approach of traffic assignment has been primarily developed to provide a more realistic and flexible theoretical framework to represent traveler’s route choice behavior in a transportation network. the problem of path overlapping in network modelling has been one of the main issues to be tackled. due to its flexible covariance structure, probit model can adequately address the pro...

A widely held viewpoint in the field of predictive biomarkers for disease holds that no single marker can provide high enough discrimination and that a panel of markers, combined in some type of algorithm, will be needed. Motivated by a recent study where 27 additional markers for ovarian cancer, many of which had good predictive value alone, failed to substantially increase the predictive abil...

In this paper we propose a new mesh reconstruction algorithm that produces a displaced subdivision mesh directly from unorganized points. The displaced subdivision surface is a new mesh representation that defines a detailed mesh with a displacement map over a smooth domain surface. This mesh representation has several benefits — compact mesh size, piecewise regular connectivity — to overcome l...

A new approach to estimate the surface curvatures from 3D triangular mesh surfaces with Gaussian curvature’s geometry interpretation is proposed in this work. Unlike previous work, the proposed method does not use local surface fitting, partial derivative computation, or oriented normal vector recovery. Instead, the Gaussian curvature is estimated at a vertex as the area of its small neighborho...

ÐWe improve the basic tensor voting formalism to infer the sign and direction of principal curvatures at each input site from noisy 3D data. Unlike most previous approaches, no local surface fitting, partial derivative computation, nor oriented normal vector recovery is performed in our method. These approaches are known to be noise-sensitive since accurate partial derivative information is oft...

With the development of high-throughput sequencing and genotyping technologies, the number of markers collected in genetic association studies is growing rapidly, increasing the importance of methods for correcting for multiple hypothesis testing. The permutation test is widely considered the gold standard for accurate multiple testing correction, but it is often computationally impractical for...