5期

最新文章

• LIMIT THEOREMS FOR WEIGHTED SAMPLES WITH APPLICATIONS TO SEQUENTIAL MONTE CARLO METHODS AI翻译
  作者：Douc, Randal; Moulines, Eric
  作者单位：Institut Polytechnique de Paris; Ecole Polytechnique
  摘要：In the last decade, sequential Monte Carlo methods (SMC) emerged as a key tool in computational statistics [see, e.g., Sequential Monte Carlo Methods in Practice (2001) Springer, New York, Monte Carlo Stratergies in Scientific Computing (2001) Springer, New York, Complex Stochastic systems (2001) 109-173]. These algorithms approximate a sequence of distributions by a sequence of weighted empirical measures associated to a weighted population of particles, which are generated recursively. Despi...
• RESIDUAL EMPIRICAL PROCESSES FOR LONG AND SHORT MEMORY TIME SERIES AI翻译
  作者：Chan, Ngai Hang; Ling, Shiqing
  作者单位：Chinese University of Hong Kong; Hong Kong University of Science & Technology
  摘要：This paper studies the residual empirical process of long- and short-memory time series regression models and establishes its uniform expansion under a general framework. The results are applied to the stochastic regression models and unstable autoregressive models. For the long-memory noise, it is shown that the limit distribution of the Kolmogorov-Smimov test statistic studied in Ho and Hsing [Ann. Statist. 24 (1996) 992-1024] does not hold when the stochastic regression model includes an un...
• AN ALGORITHMIC AND A GEOMETRIC CHARACTERIZATION OF COARSENING AT RANDOM AI翻译
  作者：Gill, Richard D.; Grunwald, Peter D.
  作者单位：Leiden University - Excl LUMC; Leiden University; Centrum Wiskunde & Informatica (CWI)
  摘要：We show that the class of conditional distributions satisfying the coarsening at random (CAR) property for discrete data has a simple and robust algorithmic description based oil randomized uniform multicovers: combinatorial objects generalizing the notion of partition of a set. However, the complexity of a given CAR mechanism can be large: the maximal height of the needed multicovers can be exponential in the number of points, in the sample space. The results stein from a geometric interpreta...
• ANALYSIS OF VARIANCE, COEFFICIENT OF DETERMINATION AND F-TEST FOR LOCAL POLYNOMIAL REGRESSION AI翻译
  作者：Huang, Li-Shan; Chen, Jianwei
  作者单位：University of Rochester; California State University System; San Diego State University
  摘要：This paper provides ANOVA inference for nonparametric local polynomial regression (LPR) in analogy with ANOVA tools for the classical linear regression model. A surprisingly simple and exact local ANOVA decomposition is established, and a local R-squared quantity is defined to measure the proportion of local variation explained by fitting LPR. A global ANOVA decomposition is obtained by integrating local counterparts, and a global R-squared and a symmetric projection matrix are defined. We sho...
• PROFILE-KERNEL LIKELIHOOD INFERENCE WITH DIVERGING NUMBER OF PARAMETERS AI翻译
  作者：Lam, Clifford; Fan, Jianqing
  作者单位：Princeton University
  摘要：The generalized varying coefficient partially linear model with a growing number of predictors arises in many contemporary scientific endeavor. In this paper we set foot on both theoretical and practical sides of profile likelihood estimation and inference. When the number of parameters grows with sample size, the existence and asymptotic normality of the profile likelihood estimator are established under some regularity conditions. Profile likelihood ratio inference for the growing number of ...
• EVALUATION OF FORMAL POSTERIOR DISTRIBUTIONS VIA MARKOV CHAIN ARGUMENTS AI翻译
  作者：Eaton, Morris L.; Hobert, James P.; Jones, Galin L.; Lai, Wen-Lin
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; State University System of Florida; University of Florida; Providence University - Taiwan
  摘要：We consider evaluation of proper posterior distributions obtained from improper prior distributions. Our context is estimating a bounded function phi of a parameter when the loss is quadratic. If the posterior mean of 0 is admissible for all bounded phi, the posterior is strongly admissible. We give sufficient conditions for strong admissibility. These conditions involve the recurrence of a Markov chain associated with the estimation problem. We develop general sufficient conditions for recurr...
• STEIN ESTIMATION FOR THE DRIFT OF GAUSSIAN PROCESSES USING THE MALLIAVIN CALCULUS AI翻译
  作者：Privault, Nicolas; Reveillac, Anthony
  作者单位：City University of Hong Kong; La Rochelle Universite
  摘要：We consider the nonparametric functional estimation of the drift of a Gaussian process via minimax and Bayes estimators. In this context, we construct superefficient estimators of Stein type for such drifts using the Malliavin integration by parts formula and superharmonic functionals on Gaussian space. Our results are illustrated by numerical simulations and extend the construction of James-Stein type estimators for Gaussian processes by Berger and Wolpert [J. Multivariate Anal. 13 (1983) 401...
• LEARNING BY MIRROR AVERAGING AI翻译
  作者：Juditsky, A.; Rigollet, P.; Tsybakov, A. B.
  作者单位：Communaute Universite Grenoble Alpes; Institut National Polytechnique de Grenoble; Universite Grenoble Alpes (UGA); Centre National de la Recherche Scientifique (CNRS); Inria; University System of Georgia; Georgia Institute of Technology; Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Mathematical Sciences (INSMI); Sorbonne Universite; Universite Paris Cite; Institut Polytechnique de Paris; ENSAE Paris
  摘要：Given a finite collection of estimators or classifiers, we study the problem of model selection type aggregation, that is, we construct a new estimator or classifier, called aggregate, which is nearly as good as the best among them with respect to a given risk criterion. We define our aggregate by a simple recursive procedure which solves an auxiliary stochastic linear programming problem related to the original nonlinear one and constitutes a special case of the mirror averaging algorithm. We...
• ROBUST NONPARAMETRIC ESTIMATION VIA WAVELET MEDIAN REGRESSION AI翻译
  作者：Brown, Lawrence D.; Cai, T. Tony; Zhou, Harrison H.
  作者单位：University of Pennsylvania; Yale University
  摘要：In this paper we develop a nonparametric regression method that is simultaneously adaptive over a wide range of function classes for the regression function and robust over a large collection of error distributions, including those that are heavy-tailed, and may not even possess variances or means. Our approach is to first use local medians to turn the problem of nonparametric regression with unknown noise distribution into a standard Gaussian regression problem and then apply a wavelet block ...
• CHOICE OF NEIGHBOR ORDER IN NEAREST-NEIGHBOR CLASSIFICATION AI翻译
  作者：Hall, Peter; Park, Byeong U.; Samworth, Richard J.
  作者单位：University of Melbourne; Seoul National University (SNU); University of Cambridge
  摘要：The kth-nearest neighbor rule is arguably the simplest and most intuitively appealing nonparametric classification procedure. However, application of this method is inhibited by lack of knowledge about its properties, in particular, about the manner in which it is influenced by the value of k; and by the absence of techniques for empirical choice of k. In the present paper we detail the way in which the value of k determines the misclassification error. We consider two models, Poisson and Bino...