The Annals of Statistics

最新文章

• The topography of multivariate normal mixtures AI翻译
  作者：Ray, S; Lindsay, BG
  作者单位：University of North Carolina; University of North Carolina Chapel Hill; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
  摘要：Multivariate normal mixtures provide a flexible method of fitting high-dimensional data. It is shown that their topography, in the sense of their key features as a density, can be analyzed rigorously in lower dimensions by use of a ridgeline manifold that contains all critical points, as well as the ridges of the density. A plot of the elevations on the ridgeline shows the key features of the mixed density. In addition, by use of the ridgeline, We uncover a function that determines the number ...
• Breakdown and groups - Rejoinder AI翻译
  作者：Davies, PL; Gather, U
  作者单位：University of Duisburg Essen; Dortmund University of Technology
• On optimality of stepdown and stepup multiple test procedures AI翻译
  作者：Lehmann, EL; Romano, JP; Shaffer, JP
  作者单位：University of California System; University of California Berkeley; Stanford University
  摘要：Consider the multiple testing problem of testing k null hypotheses, where the unknown family of distributions is assumed to satisfy a certain monotonicity assumption. Attention is restricted to procedures that control the familywise error rate in the strong sense and which satisfy a monotonicity condition. Under these assumptions, we prove certain maximin optimality results for some well-known stepdown and stepup procedures.
• Breakdown and groups - Discussion AI翻译
  作者：Tyler, DE
  作者单位：Rutgers University System; Rutgers University New Brunswick
• Likelihood approach for marginal proportional hazards regression in the presence of dependent censoring AI翻译
  作者：Zeng, DL
  作者单位：University of North Carolina; University of North Carolina Chapel Hill
  摘要：In many public health problems, an important goal is to identify the effect of some treatment/intervention on the risk of failure for the whole population. A marginal proportional hazards regression model is often used to analyze such an effect. When dependent censoring is explained by many auxiliary covariates, we utilize two working models to condense high-dimensional covariates to achieve dimension reduction. Then the estimator of the treatment effect is obtained by maximizing a pseudo-like...
• Testing convex hypotheses on the mean of a Gaussian vector. Application to testing qualitative hypotheses on a regression function AI翻译
  作者：Baraud, Y; Huet, S; Laurent, B
  作者单位：Universite Cote d'Azur; Centre National de la Recherche Scientifique (CNRS); INRAE; Universite Paris Saclay; Universite Federale Toulouse Midi-Pyrenees (ComUE); Universite de Toulouse; Institut National des Sciences Appliquees de Toulouse
  摘要：In this paper we propose a general methodology, based on multiple testing, for testing that the mean Of a Gaussian) vector in R(n) belongs to a convex set. We show that the test achieves its nominal level. and characterize a class of vectors over which the tests achieve a prescribed power, In the functional regression model this general methodology is applied to test some qualitative hypotheses oil the regression function. For example. we (est that the regression function is positive. increasi...
• A robust method for cluster analysis AI翻译
  作者：Gallegos, MT; Ritter, G
  作者单位：University of Passau
  摘要：Let there be given a contaminated list of n R-d-valued observations coming from g different, normally distributed populations with a common covariance matrix. We compute the ML-estimator with respect to a certain statistical model with n - r outliers for the parameters of the g populations it detects outliers and simultaneously partitions their complement into g clusters. It turns out that the estimator unites both the minimum-covariance-determinant rejection method and the well-known pooled d...
• From ANOVA to variance components - Discussion AI翻译
  作者：Zaslavsky, AM
  作者单位：Harvard University; Harvard Medical School
• Estimation of the density of regression errors AI翻译
  作者：Efromovich, S
  作者单位：University of New Mexico
  摘要：Estimation of the density of regression errors is a fundamental issue in regression analysis and it is typically explored via a parametric approach. This article uses a nonparametric approach with the mean integrated squared error (MISE) criterion. It solves a long-standing problem, formulated two decades ago by Mark Pinsker, about estimation of a nonparametric error density in a nonparametric regression setting with the accuracy of an oracle that knows the underlying regression errors. The So...
• Square root penalty: Adaptation to the margin in classification and in edge estimation AI翻译
  作者：Tsybakov, AB; van de Geer, SA
  作者单位：Sorbonne Universite; Universite Paris Cite; Leiden University; Leiden University - Excl LUMC
  摘要：We consider the problem of adaptation to the margin in binary classification. We suggest a penalized empirical risk minimization classifier that adaptively attains, up to a logarithmic factor, fast optimal rates of convergence for the excess risk, that is, rates that can be faster than n(-1/2), where n is the sample size. We show that our method also gives adaptive estimators for the problem of edge estimation.