The Annals of Statistics

最新文章

• Complexity regularization via localized random penalties AI翻译
  作者：Lugosi, G; Wegkamp, M
  作者单位：Pompeu Fabra University; State University System of Florida; Florida State University
  摘要：In this article, model selection via penalized empirical loss minimization in nonparametric classification problems is studied. Data-dependent penalties are constructed, which are based on estimates of the complexity of a small subclass of each model class, containing only those functions with small empirical loss. The penalties are novel since those considered in the literature are typically based on the entire model class. Oracle inequalities using these penalties are established, and the ad...
• Training samples in objective Bayesian model selection AI翻译
  作者：Berger, JO; Pericchi, LR
  作者单位：Duke University; University of Puerto Rico; University of Puerto Rico Rio Piedras
  摘要：Central to several objective approaches to Bayesian model selection is the use of training samples (subsets of the data), so as to allow utilization of improper objective priors. The most common prescription for choosing training samples is to choose them to be as small as possible, subject to yielding proper posteriors; these are called minimal training samples. When data can vary widely in terms of either information content or impact on the improper priors, use of minimal training samples c...
• Construction of E(s2)-optimal supersaturated designs AI翻译
  作者：Bulutoglu, DA; Cheng, CS
  作者单位：United States Department of Defense; United States Air Force; US Air Force Research Laboratory; Air Force Institute of Technology (AFIT); Academia Sinica - Taiwan
  摘要：Booth and Cox proposed the E(s(2)) criterion for constructing two-level supersaturated designs. Nguyen [Technometrics 38 (1996) 69-73] and Tang and Wu [Canad. J. Statist 25 (1997) 191-201] independently derived a lower bound for E(s(2)). This lower bound can be achieved only when m is a multiple of N - 1, where m is the number of factors and N is the run size. We present a method that uses difference families to construct designs that satisfy this lower bound. We also derive better lower bound...
• Nonconcave penalized likelihood with a diverging number of parameters AI翻译
  作者：Fan, JQ; Peng, H
  作者单位：Princeton University; Chinese University of Hong Kong
  摘要：A class of variable selection procedures for parametric models via nonconcave penalized likelihood was proposed by Fan and Li to simultaneously estimate parameters and select important variables. They demonstrated that this class of procedures has an oracle property when the number of parameters is finite. However, in most model selection problems the number of parameters should be large and grow with the sample size. In this paper some asymptotic properties of the nonconcave penalized likelih...
• Confidence balls in Gaussian regression AI翻译
  作者：Baraud, Y
  作者单位：Universite PSL; Ecole Normale Superieure (ENS); Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Mathematical Sciences (INSMI)
  摘要：Starting from the observation of an R(n)-Gaussian vector of mean f and covariance matrix sigma(2)I(n) (I(n) is the identity matrix), we propose a method for building a Euclidean confidence ball around f, with prescribed probability of coverage. For each n, we describe its nonasymptotic property and show its optimality with respect to some criteria.
• Least angle regression - Discussion AI翻译
  作者：Stine, RA
  作者单位：University of Pennsylvania
• Optimality of the CUSUM procedure in continuous time AI翻译
  作者：Moustakides, GV
  作者单位：Universite de Rennes; University of Thessaly
  摘要：The optimality of CUSUM under a Lorden-type criterion setting is considered. We demonstrate the optimality of the CUSUM test for lto processes, in a sense similar to Lorden's, but with a criterion that replaces expected delays by the corresponding Kullback-Leibler divergence.
• A generalized EWMA control chart and its comparison with the optimal EWMA, CUSUM and GLR schemes AI翻译
  作者：Han, D; Tsung, F
  作者单位：Shanghai Jiao Tong University; Hong Kong University of Science & Technology
  摘要：It is known that both the optimal exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) control charts are based on a given reference value delta, which, for the CUSUM chart, is the magnitude of a shift in the mean to be detected quickly. In this paper a generalized EWMA control chart (GEWMA) which does not depend on delta is proposed for detecting the mean shift. We compare theoretically the GEWMA control chart with the optimal EWMA, CUSUM and the generalized likelihood rati...
• Estimation of proportional covariances in the presence of certain linear restrictions AI翻译
  作者：Jensen, ST; Madsen, J
  作者单位：University of Copenhagen; Statens Serum Institut
  摘要：Proportionality of covariance matrices of n independent p-dimensional normal distributions with the same type of linear restrictions of the inverse covariances is considered. Conditions for existence and uniqueness of the maximum likelihood estimator are obtained through the development of general results for scale-invariant natural exponential families.
• On the posterior distribution of the number of components in a finite mixture AI翻译
  作者：Nobile, A
  作者单位：University of Glasgow
  摘要：The posterior distribution of the number of components k in a finite mixture satisfies a set of inequality constraints. The result holds irrespective of the parametric form of the mixture components and under assumptions on the prior distribution weaker than those routinely made in the literature on Bayesian analysis of finite mixtures. The inequality constraints can be used to perform an internal consistency check of MCMC estimates of the posterior distribution of k and to provide improved es...