4期

最新文章

• Interactions and outliers in the two-way analysis of variance AI翻译
  作者：Terbeck, W; Davies, PL
  作者单位：University of Duisburg Essen
  摘要：The two-way analysis of variance with interactions is a well established and integral part of statistics. In spite of its long standing, it is shown that the standard definition of interactions is counterintuitive and obfuscates rather than clarifies. A different definition of interaction is given which among other advantages allows the detection of interactions even in the case of one observation per cell. A characterization of unconditionally identifiable interaction patterns is given and it...
• 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...
• 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...
• On chain graph models for description of conditional independence structures AI翻译
  作者：Studeny, M; Bouckaert, RR
  作者单位：Czech Academy of Sciences; Institute of Information Theory & Automation of the Czech Academy of Sciences; Prague University of Economics & Business; Utrecht University
  摘要：A chain graph (CG) is a graph admitting both directed and undirected edges with (partially) directed cycles forbidden. It generalizes both the concept of undirected graph (UG) and the concept of directed acyclic graph (DAG). A chain graph can be used to describe efficiently the conditional independence structure of a multidimensional discrete probability distribution in the form of a graphoid, that is, in the form of a list of statements X is independent of Y given Z obeying a set of five prop...
• Empirical Edgeworth expansions for symmetric statistics AI翻译
  作者：Putter, H; van Zwet, WR
  作者单位：University of Amsterdam; Academic Medical Center Amsterdam; Leiden University - Excl LUMC; Leiden University
  摘要：In this paper the validity of a one-term Edgeworth expansion for Studentized symmetric statistics is proved. We propose jackknife estimates for the unknown constants appearing in the expansion and prove their consistency. As a result we obtain the second-order correctness of the empirical Edgeworth expansion for a very general class of statistics, including U-statistics, L-statistics and smooth functions of the sample mean. We illustrate the application of the bootstrap in the case of a U-stat...
• A functional central limit theorem for regression models AI翻译
  作者：Bischoff, W
  作者单位：Helmholtz Association; Karlsruhe Institute of Technology
  摘要：Let a linear regression be given. For detecting change-points, it is usual to consider the sequence of partial sums of least squares residuals whence a partial sums process is defined. Given a sequence of exact experimental designs, we consider for each design the corresponding partial sums process. If the sequence of designs converges to a continuous design, we derive the explicit form of the limit process of the corresponding sequence of partial sums processes. This is a complicated function...
• Computation of the exact information matrix of Gaussian dynamic regression time series models AI翻译
  作者：Klein, A; Mélard, G; Zahaf, T
  作者单位：University of Amsterdam; Universite Libre de Bruxelles
  摘要：In this paper, the computation of the exact Fisher information matrix of a large class of Gaussian time series models is considered. This class, which is often called the single-input-single-output (SISO) model, includes dynamic regression with autocorrelated errors and the transfer function model, with autoregressive moving average errors. The method is based on a combination of two computational procedures: recursions for the covariance matrix of the derivatives of the state vector with resp...