Gibbs sampling for marginal posterior expectations

In earlier work (Gelfand and Smith, 1990 and Gelfand et al, 1990) a sampling based approach using the Gibbs sampler was offered as a means for developing marginal posterior densities for a wide range of Bayesian problems several of which were previously inaccessible. Our purpose here is two-fold. First we flesh out the implementation of this approach for calculation of arbitrary expectations of interest. Secondly we offer comparison with perhaps the most prominent approach for calculating posterior expectations, analytic approximation involving application of the LaPlace method. Several illustrative examples are discussed as well. Clear advantages for the sampling based approach emerge.     

Tests for Symmetry Based on the One-Sample Wilcoxon Signed Rank Statistic

ABSTRACT

The one-sample Wilcoxon signed rank test was originally designed to test for a specified median, under the assumption that the distribution is symmetric, but it can also serve as a test for symmetry if the median is known. In this article we derive the Wilcoxon statistic as the first component of Pearson's X ² statistic for independence in a particularly constructed contingency table. The second and third components are new test statistics for symmetry. In the second part of the article, the Wilcoxon test is extended so that symmetry around the median and symmetry in the tails can be examined seperately. A trimming proportion is used to split the observations in the tails from those around the median. We further extend the method so that no arbitrary choice for the trimming proportion has to be made. Finally, the new tests are compared to other tests for symmetry in a simulation study. It is concluded that our tests often have substantially greater powers than most other tests.     

MULTISTAGE SAMPLING FOR RAW WOOL CHARACTERISTICS

The problem of evaluating the sampling variance of a mean when units are subsampled from a multistage sample is discussed. In particular, a specific problem arising in the sampling of wool where information on the identity of subsampled units is not available is dealt with by introducing a simple model to account for the variability in the unobserved numbers of observations within the multistage categories. Estimation aspects of the wool example are also dealt with.     

ASYMPTOTIC PROPERTIES OF RESTRICTED MAXIMUM LIKELIHOOD (REML) ESTIMATES FOR HIERARCHICAL MIXED LINEAR MODELS

This paper explores the asymptotic distribution of the restricted maximum likelihood estimator of the variance components in a general mixed model. Restricting attention to hierarchical models, central limit theorems are obtained using elementary arguments with only mild conditions on the covariates in the fixed part of the model and without having to assume that the data are either normally or spherically symmetrically distributed. Further, the REML and maximum likelihood estimators are shown to be asymptotically equivalent in this general framework, and the asymptotic distribution of the weighted least squares estimator (based on the REML estimator) of the fixed effect parameters is derived.     

TAPAS: A modular framework to support reuse in scheduling software development

Industrial schedulers try to take into account more and more complex aspects of manufacturing and become, as a consequence, more difficult to use efficiently. We suggest a modular framework for scheduling in order to support the development of schedulers better adapted to the workshop they are used in. An extensive reuse of past developments is made possible by the definition of a powerful, yet generic, data model, together with a fully modular architecture and the use of standards, e.g. CORBA, MMS and STEP. Examples of the first schedulers developed within this framework in an industrial context are shown.     

C239. The continued fraction for lnr( z): a stieljes conjecture

Estimation in logistic-normal models for correlated and overdispersed binomial data is complicated by the numerical evaluation of often intractable likelihood functions. Penalized quasilikelihood (PQL) estimators of fixed effects and variance components are known to be seriously biased for binary data. A simple correction procedure has been proposed to improve the performance of the PQL estimators. The proposed method is illustrated by analyzing infectious disease data. Its performance is compared, by means of simulations, with that of the Bayes approach using the Gibbs sampler.     

论行政文化的内容及其内在联系

行政文化是一个由多种要素组成的有机系统 ,本文旨在分析行政文化的具体内容要素 ,要素间的内在联系 ,以及这一研究对建设行政文化和更深层次探讨行政文化的重要意义     

Some New Estimators for Small-Area Means With Application to the Assessment of Farmland Values

Regression models that account for main state effects and nested county effects are considered for the assessment of farmland values. Empirical predictors obtained by replacing the unknown variances in the formulas of the optimal predictors by maximum likelihood estimates are presented. The computations are carried out by simple iterations between two SAS procedures. Estimators for the prediction variances are derived, and a modification to secure the robustness of the predictors is proposed. The procedure is applied to data on nonirrigated cropland in the Corn Belt states and is shown to yield predictors with considerably lower prediction mean squared errors than the survey estimators and other regression-type estimators.     

湖南省农业现代化评价指标体系的构建及其测定

通过主成分分析和逐步聚类分析,我们发现,2011年,长沙地区的农业现代化水平最高,属于第一层次,株洲等六个地区的农业现代化水平属于第二层次,永州等七个地区的农业现代化水平属于第三层次.整个湖南省的农业现代化水平还不高,需要进一步提高.长沙地区应提高农产品的科技含量,大力发展生态和绿色农业,株洲等地区应努力调整农业产业结构,发展农产品加工,永州等地区应着力提高农民的收入水平,生产和开发特色农产品.     

大维数据的动态条件协方差阵的估计及其应用

大维数据给传统的协方差阵估计方法带来了巨大的挑战,数据维度和噪声的影响不容忽视。本文将主成分和门限方法有效的结合,应用到DCC模型的估计中,提出了基于主成分正交补门限方法的DCC模型（poetDCC）。poetDCC模型主要通过前K个主成分来刻画高维动态条件协方差阵的信息,然后将门限函数应用在矩阵的正交补中,有效的降低了数据的维度并剔除了噪声的影响。通过模拟和实证研究发现：较DCC模型而言,poetDCC模型明显提高了高维协方差阵的估计和预测效率;并且将其应用在投资组合时,投资者获得了更高的投资收益和经济福利。