3期

最新文章

• CONSISTENT ESTIMATION OF A MIXING DISTRIBUTION AI翻译
  作者：LEROUX, BG
  摘要：A maximum-penalized-likelihood method is proposed for estimating a mixing distribution and it is shown that this method produces a consistent estimator, in the sense of weak convergence. In particular, a new proof of the consistency of maximum-likelihood estimators is given. The estimated number of components is shown to be at least as large as the true number, for large samples. Also, the large-sample limits of estimators which are constrained to have a fixed finite number of components are i...
• ORDERING DIRECTIONAL-DATA - CONCEPTS OF DATA DEPTH ON CIRCLES AND SPHERES AI翻译
  作者：LIU, RY; SINGH, K
  摘要：Three notions of depth for directional data, angular simplicial depth (ASD), angular Tukey's depth (ATD) and arc distance depth (ADD), are developed and studied. The empirical versions of these depths give rise to center-outward rankings of angular data which may be regarded as extensions of the usual center-outward ranking on the line. Three medians derived from these depths are examined and compared. Applications in nonparametric classification and in implementing the bootstrap to construct ...
• A LOG-LINEAR MODEL FOR A POISSON-PROCESS CHANGE POINT AI翻译
  作者：LOADER, CR
  摘要：Many methods have been proposed for modelling nonhomogeneous Poisson processes, including change point models and log-linear models. In this paper, we use likelihood ratio tests to choose which of these models are necessary. Of particular interest is the test for the presence of a change point, for which standard asymptotic theory is not valid. Large deviation methods are applied to approximate the significance level, and power approximations are given. Confidence regions for the change point ...
• TESTING STATIONARITY IN THE MEAN OF AUTOREGRESSIVE PROCESSES WITH A NONPARAMETRIC REGRESSION TREND AI翻译
  作者：MILBRODT, H
  摘要：In this paper, we suggest tests of stationarity in the mean of autoregressive time series versus arbitrary trend alternatives. As an intermediate, though essential, step local asymptotic normality of autoregressive models with a nonparametric regression trend is established. Moreover, a functional central limit theorem for the underlying likelihood ratio processes is derived. These results then offer a general construction principle by which every goodness of fit test (case 0), which is based ...
• SOME ASPECTS OF POLYA TREE DISTRIBUTIONS FOR STATISTICAL MODELING AI翻译
  作者：LAVINE, M
  摘要：Polya tree distributions are defined. They are generalizations of Dirichlet processes that allow for the possibility of putting positive mass on the Bet of continuous distributions. Predictive and posterior distributions are explained. A canonical construction of a Polya tree is given so that the Polya tree has any desired predictive distribution. Choices of the Polya tree parameters are discussed. Mixtures of Polya trees are defined and examples are given.
• STATISTICAL TOOLS TO ANALYZE DATA REPRESENTING A SAMPLE OF CURVES AI翻译
  作者：KNEIP, A; GASSER, T
  作者单位：Central Institute of Mental Health
  摘要：The paper is concerned with data representing a sample of smooth curves which can be considered as independent realizations of an underlying biological (chemical,...) process. Such samples of curves often the following features: There is a typical structural pattern common to all curves of the sample. On the other hand, individual realizations of the typical shape show different dynamics and intensity. In particular, typical peaks are shifted from individual to individual. Differences in dynam...
• VARIABLE KERNEL DENSITY-ESTIMATION AI翻译
  作者：TERRELL, GR; SCOTT, DW
  作者单位：Rice University
  摘要：We investigate some of the possibilities for improvement of univariate and multivariate kernel density estimates by varying the window over the domain of estimation, pointwise and globally. Two general approaches are to vary the window width by the point of estimation and by point of the sample observation. The first possibility is shown to be of little efficacy in one variable. In particular, nearest-neighbor estimators in all versions perform poorly in one and two dimensions, but begin to be...
• SOME NONASYMPTOTIC BOUNDS FOR L1 DENSITY-ESTIMATION USING KERNELS AI翻译
  作者：DATTA, S
  摘要：In this paper we obtain uniform upper bounds for the L1 error of kernel estimators in estimating monotone densities and densities of bounded variation. The bounds are nonasymptotic and optimal in n, the sample size. For the bounded variation class, it is also optimal wrt an upper bound of the total variation. The proofs employ a one-sided kernel technique and are extremely simple.
• THE METRICALLY TRIMMED MEAN AS A ROBUST ESTIMATOR OF LOCATION AI翻译
  作者：KIM, SJ
  作者单位：University of California System; University of California Berkeley
  摘要：The metrically trimmed mean is defined as the average of observations remaining after a fixed number of outlying observations have been removed. A metric, the distance from the median, is used to determine which points are outlying. The influence curve and the asymptotic normality of the metrically trimmed mean are derived using von Mises expansions. The relative merits of the median, the trimmed mean and the metrically trimmed mean are discussed in neighborhoods of nonparametric models with n...
• A RANK STATISTICS APPROACH TO THE CONSISTENCY OF A GENERAL BOOTSTRAP AI翻译
  作者：MASON, DM; NEWTON, MA
  作者单位：University of Wisconsin System; University of Wisconsin Madison
  摘要：A general notion of a bootstrapped mean constructed by exchangeably weighting sample points is introduced. Consistency of this generalized bootstrapped mean, which includes proposals of Efron and Rubin among others, is proved by classical linear rank statistics theory. The consistency of generalized bootstrapped empirical and quantile processes is also established.