Nouveau critère de segmentation pour des variables à expliquer qualitative ordinale et quantitative multidimensionnelle
Nuclei segmentation for computer-aided diagnosis of breast cancer
Null distribution of multiple correlation coefficient under mixture normal model.
Numerical methods for linear minimax estimation
We discuss two numerical approaches to linear minimax estimation in linear models under ellipsoidal parameter restrictions. The first attacks the problem directly, by minimizing the maximum risk among the estimators. The second method is based on the duality between minimax and Bayes estimation, and aims at finding a least favorable prior distribution.
Numerical taxonomy: a missing link for case-based reasoning and autonomous agents.
Numerical taxonomy, which uses numerical methods to classify and relate items whose properties are non-numerical, is suggested as both an advantageous tool to support case-based reasoning and a means for agents to exploit knowledge that is best expressed in cases. The basic features of numerical taxonomy are explained, and discussed in application to a problem where human agents with differing views obtain solutions by negotiation and by reference to knowledge that is essentially case-like: allocation...
On a class of estimators in a multivariate RCA(1) model
This work deals with a multivariate random coefficient autoregressive model (RCA) of the first order. A class of modified least-squares estimators of the parameters of the model, originally proposed by Schick for univariate first-order RCA models, is studied under more general conditions. Asymptotic behavior of such estimators is explored, and a lower bound for the asymptotic variance matrix of the estimator of the mean of random coefficient is established. Finite sample properties are demonstrated...
On a conditional Cauchy functional equation of several variables and a characterization of multivariate stable distributions.
On a distance between estimable functions.
In this paper we study the main properties of a distance introduced by C.M. Cuadras (1974). This distance is a generalization of the well-known Mahalanobis distance between populations to a distance between parametric estimable functions inside the multivariate analysis of variance model. Reduction of dimension properties, invariant properties under linear automorphisms, estimation of the distance, distribution under normality as well as the interpretation as a geodesic distance are studied and...
On a general structure of the bivariate FGM type distributions
In this paper, we study a general structure for the so-called Farlie-Gumbel-Morgenstern (FGM) family of bivariate distributions. Through examples we show how to use the proposed structure to study dependence properties of the FGM type distributions by a general approach.
On a method of ordering and clustering of objects
On a probability inequality for multivariate normal distribution
On a problem by Schweizer and Sklar
We give a representation of the class of all -dimensional copulas such that, for a fixed , , all their -dimensional margins are equal to the independence copula. Such an investigation originated from an open problem posed by Schweizer and Sklar.
On a Statistical measure of Discrimination
On a zonal polynomial integral.
On an asymmetric extension of multivariate Archimedean copulas based on quadratic form
An important topic in Quantitative Risk Management concerns the modeling of dependence among risk sources and in this regard Archimedean copulas appear to be very useful. However, they exhibit symmetry, which is not always consistent with patterns observed in real world data. We investigate extensions of the Archimedean copula family that make it possible to deal with asymmetry. Our extension is based on the observation that when applied to the copula the inverse function of the generator of an...
On approximations of transformed chi-squared distributions in statistical applications.
On asymmetric distributions of copula related random variables which includes the skew-normal ones
Assuming that is the copula function of and with marginal distribution functions and , in this work we study the selection distribution . We present some special cases of our proposed distribution, among them, skew-normal distribution as well as normal distribution. Some properties such as moments and moment generating function are investigated. Also, some numerical analysis is presented for illustration.
On Bartlett's test for correlation between time series
An explicit formula for the correlation coefficient in a two-dimensional AR(1) process is derived. Approximate critical values for the correlation coefficient between two one-dimensional AR(1) processes are tabulated. They are based on Bartlett’s approximation and on an asymptotic distribution derived by McGregor. The results are compared with critical values obtained from a simulation study.
On best affine unbiased covariance-preserving prediction of factor scores.
This paper gives a generalization of results presented by ten Berge, Krijnen,Wansbeek & Shapiro. They examined procedures and results as proposed by Anderson & Rubin, McDonald, Green and Krijnen, Wansbeek & ten Berge.We shall consider the same matter, under weaker rank assumptions. We allow some moments, namely the variance Ω of the observable scores vector and that of the unique factors, Ψ, to be singular. We require T' Ψ T > 0, where T Λ T' is a Schur decomposition of Ω. As...
On certain transformations of Archimedean copulas: Application to the non-parametric estimation of their generators
We study the impact of certain transformations within the class of Archimedean copulas. We give some admissibility conditions for these transformations, and define some equivalence classes for both transformations and generators of Archimedean copulas. We extend the r-fold composition of the diagonal section of a copula, from r ∈ N to r ∈ R. This extension, coupled with results on equivalence classes, gives us new expressions of transformations and generators. Estimators deriving directly from these...