The Annals of Statistics

最新文章

• A stochastic process approach to false discovery control AI翻译
  作者：Genovese, C; Wasserman, L
  作者单位：Carnegie Mellon University
  摘要：This paper extends the theory of false discovery rates (FDR) pioneered by Benjamini and Hochberg [J. Roy. Statist. Soc. Set. B 57 (1995) 289-300]. We develop a framework in which the False Discovery Proportion (FDP)-the number of false rejections divided by the number of rejections-is treated as a stochastic process. After obtaining the limiting distribution of the process, we demonstrate the validity of a class of procedures I-or controlling the False Discovery Rate (the expected FDP). We con...
• Rank-based optimal tests of the adequacy of an elliptic VARMA model AI翻译
  作者：Hallin, M; Paindaveine, D
  作者单位：Universite Libre de Bruxelles
  摘要：We are deriving optimal rank-based tests for the adequacy of a vector autoregressive-moving average (VARMA) model with elliptically contoured innovation density. These tests are based on the ranks of pseudo-Mahalanobis distances and on normed residuals computed from Tyler's [Ann. Statist. 15 (1987) 234-251] scatter matrix; they generalize the univariate signed rank procedures proposed by Hallin and Puri [J. Multivariate Anal. 39 (1991) 1-29]. Two types of optimality properties are considered, ...
• The golden chain - Discussion AI翻译
  作者：Bühlmann, P; Yu, B
  作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich; University of California System; University of California Berkeley
  摘要：Jiang, Lugosi and Vayatis, and Zhang ought to be congratulated for their different works on the original AdaBoost algorithm with early stopping (Jiang), an l(1)-penalized version of boosting (Lugosi and Vayatis) and a convex minimization method which can be viewed as an l(2)-penalized version of boosting (Zhang).
• Central limit theorem for sequential Monte Carlo methods and its application to bayesian inference AI翻译
  作者：Chopin, N
  作者单位：University of Bristol
  摘要：The term sequential Monte Carlo methods or, equivalently, particle filters, refers to a general class of iterative algorithms that performs Monte Carlo approximations of a given sequence of distributions of interest (pi(t)). We establish in this paper a central limit theorem for the Monte Carlo estimates produced by these computational methods. This result holds under minimal assumptions on the distributions pi(t), and applies in a general framework which encompasses most of the sequential Mon...
• Equivalence theory for density estimation, Poisson processes and Gaussian white noise with drift AI翻译
  作者：Brown, LD; Carter, AV; Low, MG; Zhang, CH
  作者单位：University of Pennsylvania; Rutgers University System; Rutgers University New Brunswick; University of California System; University of California Santa Barbara
  摘要：This paper establishes the global asymptotic equivalence between a Poisson process with variable intensity and white noise with drift under sharp smoothness conditions on the unknown function. This equivalence is also extended to density estimation models by Poissonization. The asymptotic equivalences are established by constructing explicit equivalence mappings. The impact of such asymptotic equivalence results is that an investigation in one of these nonparametric models automatically yields...
• Asymptotic global robustness in Bayesian decision theory AI翻译
  作者：Abraham, C; Cadre, B
  作者单位：Institut Agro; Montpellier SupAgro; INRAE; Arts et Metiers Institute of Technology; Universite de Montpellier
  摘要：In Bayesian decision theory, it is known that robustness with respect to the loss and the prior can be improved by adding new observations. In this article we study the rate of robustness improvement with respect to the number of observations n. Three usual measures of posterior global robustness are considered: the (range of the) Bayes actions set derived from a class of loss functions, the maximum regret of using a particular loss when the subjective loss belongs to a given class and the ran...
• Minimax estimation of linear functionals over nonconvex parameter spaces AI翻译
  作者：Cai, TT; Low, MG
  作者单位：University of Pennsylvania
  摘要：The minimax theory for estimating linear functionals is extended to the case of a finite union of convex parameter spaces. Upper and lower bounds for the minimax risk can still be described in terms of a modulus of continuity. However in contrast to the theory for convex parameter spaces rate optimal procedures are often required to be nonlinear. A construction of such nonlinear procedures is given. The results developed in this paper have important applications to the theory of adaptation.
• Least angle regression AI翻译
  作者：Efron, B; Hastie, T; Johnstone, I; Tibshirani, R
  作者单位：Stanford University
  摘要：The purpose of model selection algorithms such as All Subsets, Forward Selection and Backward Elimination is to choose a linear model on the basis of the same set of data to which the model will be applied. Typically we have available a large collection of possible covariates from which we hope to select a parsimonious set for the efficient prediction of a response variable. Least Angle Regression (LARS), a new model selection algorithm, is a useful and less greedy version of traditional forwa...
• Selecting optimal multistep predictors for autoregressive processes of unknown order AI翻译
  作者：Ing, CK
  作者单位：Academia Sinica - Taiwan
  摘要：We consider the problem of choosing the optimal (in the sense of mean-squared prediction error) multistep predictor for an autoregressive (AR) process of finite but unknown order. If a working AR model (which is possibly misspecified) is adopted for multistep predictions, then two competing types of multistep predictors (i.e., plug-in and direct predictors) can be obtained from this model. We provide some interesting examples to show that when both plug-in and direct predictors are considered,...
• Least angle regression - Discussion AI翻译
  作者：Ishwaran, H
  作者单位：Cleveland Clinic Foundation