The Annals of Statistics

最新文章

• Bayesian goodness-of-fit testing using infinite-dimensional exponential families AI翻译
  作者：Verdinelli, I; Wasserman, L
  作者单位：Sapienza University Rome; Carnegie Mellon University
  摘要：dWe develop a nonparametric Bayes factor for testing the fit of a parametric model. We begin with a nominal parametric family which we then embed into an infinite-dimensional exponential family. The new model then has a parametric and nonparametric component. We give the log density of the nonparametric component a Gaussian process prior. An asymptotic consistency requirement puts a restriction on the form of the prior, leaving us with a single hyperparameter for which we suggest a default val...
• Directional tests for one-sided alternatives in multivariate models AI翻译
  作者：Cohen, A; Sackrowitz, HB
  作者单位：Rutgers University System; Rutgers University New Brunswick
  摘要：Consider one-sided testing problems for a multivariate exponential family model. Through conditioning or other considerations, the problem oftentimes reduces to testing a null hypothesis that the natural parameter is a zero vector against the alternative that the natural parameter lies in a closed convex cone l. The problems include testing homogeneity of parameters, testing independence in contingency tables, testing stochastic ordering of distributions and many others. A test methodology is ...
• Functional stability of one-step GM-estimators in approximately linear regression AI翻译
  作者：Simpson, DG; Yohai, VJ
  作者单位：University of Illinois System; University of Illinois Urbana-Champaign; University of Buenos Aires; Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET)
  摘要：This paper provides a comparative sensitivity analysis of one-step Newton-Raphson estimators for linear regression. Such estimators have been proposed as a way to combine the global stability of high breakdown estimators with the local stability of generalized maximum likelihood estimators. We analyze this strategy, obtaining upper bounds for the maximum bias induced by epsilon-contamination of the model. These bounds yield breakdown points and local rates of convergence of the bias as epsilon...
• Tolerance regions and multiple-use confidence regions in multivariate calibration AI翻译
  作者：Mathew, T; Sharma, MK; Nordström, K
  作者单位：University System of Maryland; University of Maryland Baltimore; Johnson & Johnson; Johnson & Johnson USA; University of Helsinki
  摘要：Let y(i) similar to N(Bx(i), Sigma), i = 1, 2,..., N, and y similar to N(B theta, Sigma) be independent multivariate observations, where the x(i)'s are known vectors, B, theta and Sigma are unknown, B being a positive definite matrix. The calibration problem deals with statistical inference concerning theta and the problem that we have addressed is the construction of confidence regions. In this article, we have constructed a region for theta based on a criterion similar to that satisfied by a...
• Constructions of random distributions via sequential barycenters AI翻译
  作者：Hill, T; Monticino, M
  作者单位：University System of Georgia; Georgia Institute of Technology; University of North Texas System; University of North Texas Denton
  摘要：This article introduces and develops a constructive method for generating random probability measures with a prescribed mean or distribution of the means. The method involves sequentially generating an array of barycenters which uniquely defines a probability measure. Basic properties of the generated measures are presented, including conditions under which almost all the generated measures are continuous or almost all are purely discrete or almost all have finite support. Applications are giv...
• Arcing classifiers - Rejoinder AI翻译
  作者：Breiman, L
  作者单位：University of California System; University of California Berkeley
• Arcing classifiers - Discussion AI翻译
  作者：Dietterich, TG
  作者单位：Oregon State University
• Block threshold rules for curve estimation using kernel and wavelet methods AI翻译
  作者：Hall, P; Kerkyacharian, G; Picard, D
  作者单位：Australian National University; Universite de Picardie Jules Verne (UPJV); Universite Paris Cite
  摘要：Motivated by recently developed threshold rules for wavelet estimators, we suggest threshold methods for general kernel density estimators, including those of classical Rosenblatt-Parzen type. Thresholding makes kernel methods competitive in terms of their adaptivity to a wide variety of aberrations in complex signals. It is argued that term-by-term thresholding does not always produce optimal performance, since individual coefficients cannot be estimated sufficiently accurately for reliable d...
• Weak convergence of the sequential empirical processes of residuals in nonstationary autoregressive models AI翻译
  作者：Ling, SQ
  作者单位：University of Hong Kong; University of Western Australia
  摘要：This paper establishes the weak convergence of the sequential empirical process (K) over bar(n) of the estimated residuals in nonstationary autoregressive models. Under some regular conditions, it is shown that (K) over bar(n) converges weakly to a Kiefer process when the characteristic polynomial does not include the unit root 1; otherwise (K) over bar(n) converges weakly to a Kiefer process plus a functional of stochastic integrals in terms of the standard Brownian motion. The latter differs...
• Asymptotically efficient estimation in the Wicksell problem AI翻译
  作者：Golubev, GK; Levit, BY
  作者单位：Russian Academy of Sciences; Utrecht University
  摘要：We consider the classical Wicksell problem of estimating an unknown distribution function G of the radii of balls, based on their observed cross-sections. It is assumed that the underlying distribution function G belongs to a Holder class of smoothness gamma > 1/2. We prove that, for a suitable choice of the smoothing parameters, kernel-type estimators are asymptotically efficient for a large class of symmetric bowl-shaped loss functions.