-
作者：Zuo, YJ; Cui, HJ
作者单位：Michigan State University; Beijing Normal University
摘要：General depth weighted scatter estimators are introduced and investigated. For general depth functions, we find out that these affine equivariant scatter estimators are Fisher consistent and unbiased for a wide range of multivariate distributions, and show that the sample scatter estimators are strong and root n-consistent and asymptotically normal, and the influence functions of the estimators exist and are bounded in general. We then concentrate on a specific case of the general depth weight...
-
作者：Maaouia, F; Touati, A
作者单位：Universite de Tunis-El-Manar; Faculte des Sciences de Tunis (FST)
摘要：We solve the problem of constructing an asymptotic global confidence region for the means and the covariance matrices of the reproduction distributions involved in a supercritical multitype branching process. Our approach is based on a central limit theorem associated with a quadratic law of large numbers performed by the maximum likelihood or the multidimensional Lotka-Nagaev estimator of the reproduction law means. The extension of this approach to the least squares estimator of the mean mat...
-
作者：Loh, WL
作者单位：National University of Singapore; University of Michigan System; University of Michigan
摘要：Stein [Statist. Sci. 4 (1989) 432-433] proposed the Matern-type Gaussian random fields as a very flexible class of models for computer experiments. This article considers a subclass of these models that are exactly once mean square differentiable. In particular, the likelihood function is determined in closed form, and under mild conditions the sieve maximum likelihood estimators for the parameters of the covariance function are shown to be weakly consistent with respect to fixed-domain asympt...
-
作者：Li, B; Zha, HY; Chiaromonte, F
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：We propose a novel approach to sufficient dimension reduction in regression, based on estimating contour directions of small variation in the response. These directions span the orthogonal complement of the minimal space relevant for the regression and can be extracted according to two measures of variation in the response, leading to simple and general contour regression (SCR and GCR) methodology. In comparison with existing sufficient dimension reduction techniques, this contour-based method...
-
作者：Romano, JP
作者单位：Stanford University
摘要：In this paper we consider the construction of optimal tests of equivalence hypotheses. Specifically, assume X-1,..., X-n are i.i.d. with distribution P theta, with theta is an element of R-k. Let g(theta) be some real-valued parameter of interest. The null hypothesis asserts g(theta) is an element of (a, b) versus the alternative g(theta) is an element of (a, b). For example, such hypotheses occur in bioequivalence studies where one may wish to show two drugs, a brand name and a proposed gener...
-
作者：Cai, TT; Low, MG
作者单位：University of Pennsylvania
摘要：A theory of superefficiency and adaptation is developed under flexible performance measures which give a multiresolution view of risk and bridge the gap between pointwise and global estimation, This theory provides a useful benchmark for the evaluation of spatially adaptive estimators and shows that the possible degree or superefficiency for minimax rate optimal estimators critically depends on the size of the neighborhood over which the risk is measured. Wavelet procedures are given which ada...
-
作者：Dryden, IL
作者单位：University of Nottingham
摘要：We consider the statistical analysis of data on high-dimensional spheres and shape spaces. The work is of particular relevance to applications where high-dimensional data are available-a commonly encountered situation in many disciplines. First the uniform measure on the infinite-dimensional sphere is reviewed, together with connections with Wiener measure. We then discuss densities of Gaussian measures with respect to Wiener measure. Some nonuniform distributions on infinite-dimensional spher...
-
作者：Johnstone, IM; Silverman, BW
作者单位：Stanford University; University of Oxford
摘要：This paper explores a class of empirical Bayes methods for level-dependent threshold selection in wavelet shrinkage. The prior considered for each wavelet coefficient is a mixture of an atom of probability at zero and a heavy-tailed density. The mixing weight, or sparsity parameter, for each level of the transform is chosen by marginal maximum likelihood. If estimation is carried out using the posterior median, this is a random thresholding procedure; the estimation can also be carried out usi...
-
作者：Maruyama, Y; Strawderman, WE
作者单位：University of Tokyo; Rutgers University System; Rutgers University New Brunswick
摘要：Let y = A beta + epsilon, where y is an N x 1 vector of observations, beta is a p x I vector of unknown regression coefficients, A is an N x p design matrix and E is a spherically symmetric error term with unknown scale parameter a. We consider estimation of under general quadratic loss functions, and, in particular, extend the work of Strawderman [J. Amer Statist. Assoc. 73 (1978) 623-627] and Casella [Ann. Statist. 8 (1980) 1036-1056, J. Amer. Statist. Assoc. 80 (1985) 753-758] by finding ad...
-
作者：Boissy, Y; Bhattacharyya, BB; Li, X; Richardson, GD
作者单位：State University System of Florida; University of Central Florida; North Carolina State University
摘要：A binomial-type operator on a stationary Gaussian process is introduced in order to model long memory in the spatial context. Consistent estimators of model parameters are demonstrated. In particular, it is shown that (d) over cap (N) - d = Op((Log N)3)/(N)), where d = (d(1), d(2)) denotes the long memory parameter.
