Showing papers in "Journal of Multivariate Analysis in 2001"

TL;DR: In this article, a general class of multivariate skew-elliptical distributions is proposed, which contains the multivariate normal, Student's t, exponential power, and Pearson type II, with an extra parameter to regulate skewness.

TL;DR: In this article, a two-step subsample bootstrap method is used to adaptively select the sample fraction that minimizes the asymptotic mean-squared error.

TL;DR: In this article, the notion of principal oriented points is introduced, and the existence of principal curves passing through these points is proved, leading to a generalization of the definition of total variance.

TL;DR: This work derives a closed form expression for the copula-graphic estimator when the joint survival function is modeled with an Archimedean copula and shows it to be uniformly consistent and asymptotically normal.

TL;DR: In this article, nonparametric tests of independence that can be used to test the independence of p random variables, serial independence for time series, or residuals data are presented.

TL;DR: In this article, the authors show that under some regularity conditions, the Kaplan?Meier estimator enjoys uniform consistency with rates, and a stochastic process generated by the Kmeier?Meiers estimator converges weakly to a certain Gaussian process with a specified covariance structure.

TL;DR: In this paper, the authors show that minimax and shrinkage estimators under a normal distribution remain robust under an elliptically contoured distribution for both invariant and non-invariant loss functions in a multivariate linear regression model.

TL;DR: In this paper, it is shown how known algorithms for the comparison of all variables subsets in regression analysis can be adapted to subset comparisons in multivariate analysis, according to any index based on Wilks, Lawley?Hotelling, or Bartllet?Pillai statistics.

TL;DR: In this paper, the central limit theorem and weak convergence for sums?j = 1nfSj(l)l,n?1, under some suitable conditions, were investigated.

TL;DR: In this article, the authors proposed a new componentwise estimator of a dispersion matrix, based on a highly robust estimators of scale, which is the elimination of a location estimator in the dispersion estimation procedure.

TL;DR: In this paper, an empirical log-likelihood ratio for β is proposed and shown to have a limiting distribution of a weighted sum of independent chi-square distributions, which can be used to construct an approximate confidence region for β.

TL;DR: In this paper, the problems of testing a normal covariance matrix and an interval estimation of generalized variance when the data are missing from subsets of components are considered, and an approximate confidence interval for the generalized variance is given.

TL;DR: In this paper, the authors show that for all possible types of kernels, symmetric, antisymmetric, degenerate, non-degenerate, the test statistics are asymptotically normally distributed.

TL;DR: In this article, the dependence function of a bivariate extreme survival function with standard exponential marginals is estimated using nonparametric estimators and their strong uniform convergence under suitable conditions is demonstrated.

TL;DR: In this article, the marginal quasi-likelihood (MQL) method was proposed for estimating the parameters of the generalized linear mixed models (GLMMs) based on the joint moments of order up to four.

TL;DR: In this paper, the authors consider a class of logistic models for case-control studies with a partially observed covariate, where the likelihood is a combination of a nonparametric mixture, a parametric likelihood, and an empirical likelihood.

TL;DR: In this paper, the authors discuss some methods to test for possible changes in the parameters of a long-memory sequence and obtain the limit distributions of the test statistics under the no-change null hypothesis.

TL;DR: In this paper, the authors provide a general framework for studying the correlation structure of shock models in the setup of a multivariate, correlated counting process and to systematically develop upper and lower bounds for its joint component lifetime distribution and survival functions.

TL;DR: In this paper, the sensitivity of half-space depth values and contours to perturbations of the underlying distribution is investigated, and the influence function of the halfspace depth of any point x?Rp is bounded and discontinuous.

TL;DR: In this article, different test statistics based on integrated quadratic forms measuring the proximity between fn, a kernel estimator of f, and f0, or between fn and its expected value computed under H0 were considered.

TL;DR: For the Rayleigh and Bingham tests of uniformity on spheres of arbitrary dimension, Stiefel manifolds, rotation groups, Grassmann manifolds and complex projective spaces, the authors calculated modifications of score test statistics which brought the null distributions close to their large-sample asymptotic distributions.

TL;DR: In this article, a simple consistent test is developed which is based on the difference between the corresponding sum of squares of the ordinary ANOVA for the multi-factor case and a nonparametric variance estimator.

TL;DR: The Chung?Smirnov law and the Finkelstein functional law of the iterated logarithm for empirical processes are used to establish new results on the central limit theorem as mentioned in this paper.

TL;DR: In this paper, failure rates and mean residual life function of the marginal distributions and their monotonic properties are studied and the hazard components and their properties are investigated and their relationships with some measures of dependence are established.

TL;DR: The pairwise-only dependence assumption is relaxed, and the necessary form that one-parameter exponential family conditional densities must take under more general conditions of multiway dependence is given.

TL;DR: In this article, a class of robust estimators which are characterized as eigenvectors of weighted sample covariance matrices is proposed, where the weight functions recursively depend on the eigenvesctors themselves.

TL;DR: In this paper, the problem of discriminating, on the basis of random "training" samples, between two independent multivariate normal populations, Np(?,?1) and Np (?,?2), which have a common mean vector and distinct covariance matrices?1 and?2, was considered.

TL;DR: In this paper, a complete characterization of the spectrum of locally square integrable periodically correlated (PC) processes is obtained, which makes use of the author's recent theorem establishing a one to one correspondence between PC processes and a certain class on infinite dimensional stationary processes.

TL;DR: In this article, an adjusted empirical likelihood inference and a martingale-based bootstrap inference for the mean difference were derived, and the corresponding empirical likelihood confidence interval of the mean-difference estimator was constructed.

TL;DR: In this article, the authors generalized the expectation formula to the singular and non-singular multivariate Dirichlet distributions on symmetric cones, and obtained a result parallel to that given above for the univariate case.