Classical Statistical Analysis Based on a Certain Hypercomplex Multivariate Normal Distribution.
Conditions for Invariance of the Multivariate Versions of Grubb's Test and Bartlett's Test. Under a General Dependency Structure.
Construction of multivariate distributions: a review of some recent results.
The construction of multivariate distributions is an active field of research in theoretical and applied statistics. In this paper some recent developments in this field are reviewed. Specifically, we study and review the following set of methods: (a) Construction of multivariate distributions based on order statistics, (b) Methods based on mixtures, (c) Conditionally specified distributions, (d) Multivariate skew distributions, (e) Distributions based on the method of the variables in common and...
Criterio para detectar outliers en poblaciones normales bivariantes.
Damos un procedimiento de detección de outliers para muestras procedentes de poblaciones normales bivariantes, que viene dado por el cuadrado de la distancia entre matrices de sumas de cuadrados y sumas de productos de observaciones muestrales, la cual se ha obtenido a partir de la forma métrica diferencial de Maas.
Defects and transformations of quasi-copulas
Six different functions measuring the defect of a quasi-copula, i. e., how far away it is from a copula, are discussed. This is done by means of extremal non-positive volumes of specific rectangles (in a way that a zero defect characterizes copulas). Based on these defect functions, six transformations of quasi-copulas are investigated which give rise to six different partitions of the set of all quasi-copulas. For each of these partitions, each equivalence class contains exactly one copula being...
Densities of determinant ratios, their moments and some simultaneous confidence intervals in the multivariate Gauss-Markoff model
The following three results for the general multivariate Gauss-Markoff model with a singular covariance matrix are given or indicated. determinant ratios as products of independent chi-square distributions, moments for the determinants and the method of obtaining approximate densities of the determinants.
Detection of influential points by convex hull volume minimization
A method of geometrical characterization of multidimensional data sets, including construction of the convex hull of the data and calculation of the volume of the convex hull, is described. This technique, together with the concept of minimum convex hull volume, can be used for detection of influential points or outliers in multiple linear regression. An approximation to the true concept is achieved by ordering the data into a linear sequence such that the volume of the convex hull of the first...
Discrete generalized Liouville-type distribution and related multivariate distributions.
Discrete analogue of the Liouville distribution is defined and is termed as Discrete Generalized Liouville-Type Distribution (DGL-TD). Firstly, properties in its factorial and ordinary moments are given. Then by finding the covariance matrix, partial and multiple correlations for DGL-TD are evaluated. Multinomial, multivariate negative binomial and multivariate log series distributions are shown as particular cases of this general distribution. The asymptotic distribution of the estimates of the...
Distribución del cuadrado de la máxima correlación canónica para tamaños muestrales pequeños.
Distribution of LRC for testing sphericity of a complex multivariate Gaussian model.
Elliptische Streuflächen ebener Punkthaufen.
Estimation and tests in finite mixture models of nonparametric densities
The aim is to study the asymptotic behavior of estimators and tests for the components of identifiable finite mixture models of nonparametric densities with a known number of components. Conditions for identifiability of the mixture components and convergence of identifiable parameters are given. The consistency and weak convergence of the identifiable parameters and test statistics are presented for several models.
Estimation du support et du contour du support d'une loi de probabilité
Estimation of parameters of a spherical invariant stable distribution
This paper concerns the estimation of the parameters that describe spherical invariant stable distributions: the index α ∈ (0,2] and the scale parameter σ >0. We present a kind of moment estimators derived from specially transformed original data.
Estimators and tests for variance components in cross nested orthogonal designs
Explicit expressions of UMVUE for variance components are obtained for a class of models that include balanced cross nested random models. These estimators are used to derive tests for the nullity of variance components. Besides the usual F tests, generalized F tests will be introduced. The separation between both types of tests will be based on a general theorem that holds even for mixed models. It is shown how to estimate the p-value of generalized F tests.
Exact distribution for the generalized F tests
Generalized F statistics are the quotients of convex combinations of central chi-squares divided by their degrees of freedom. Exact expressions are obtained for the distribution of these statistics when the degrees of freedom either in the numerator or in the denominator are even. An example is given to show how these expressions may be used to check the accuracy of Monte-Carlo methods in tabling these distributions. Moreover, when carrying out adaptative tests, these expressions enable us to estimate...
Exponential bounds for multivariate self-normalized sums.
Extreme distribution functions of copulas
In this paper we study some properties of the distribution function of the random variable C(X,Y) when the copula of the random pair (X,Y) is M (respectively, W) – the copula for which each of X and Y is almost surely an increasing (respectively, decreasing) function of the other –, and C is any copula. We also study the distribution functions of M(X,Y) and W(X,Y) given that the joint distribution function of the random variables X and Y is any copula.
Gaussian approximation of Gaussian scale mixtures
For a given positive random variable and a given independent of , we compute the scalar such that the distance in the sense between and is minimal. We also consider the same problem in several dimensions when is a random positive definite matrix.
Generalized logistic model and its orthant tail dependence
The Multivariate Extreme Value distributions have shown their usefulness in environmental studies, financial and insurance mathematics. The Logistic or Gumbel-Hougaard distribution is one of the oldest multivariate extreme value models and it has been extended to asymmetric models. In this paper we introduce generalized logistic multivariate distributions. Our tools are mixtures of copulas and stable mixing variables, extending approaches in Tawn [14], Joe and Hu [6] and Fougères et al. [3]. The...