A double Metropolis–Hastings sampler for spatial models with intractable normalizing constants

The problem of simulating from distributions with intractable normalizing constants has received much attention in recent literature. In this article, we propose an asymptotic algorithm, the so-called double Metropolis–Hastings (MH) sampler, for tackling this problem. Unlike other auxiliary variable algorithms, the double MH sampler removes the need for exact sampling, the auxiliary variables being generated using MH kernels, and thus can be applied to a wide range of problems for which exact sampling is not available. For the problems for which exact sampling is available, it can typically produce the same accurate results as the exchange algorithm, but using much less CPU time. The new method is illustrated by various spatial models.     

谈几类中值定理辅助函数的构造方法

给出三类中值定理辅助函数的构造方法.     

从《金瓶梅》看补语演变的向心趋势

<金瓶梅>含有补语的句子中动语、宾语和补语的语序与现代汉语的情况很不相同.比较之后,可以看出补语演变过程中的向心趋势.补语对中心语具有向心力是语义表达的客观要求,句子结构要求平衡可能也是一个原因.     

基于城乡统筹的环城高速公路公共交通运营的建设与管理

分析了在环城高速公路上增设公共交通运营方式的作用,提出了在环城高速公路上建设公共交通运营方式的思路,并针对其建设与管理的方法进行了一定的研究,为完善城乡交通网络,促进城乡统筹发展提供了很好的策略方法。     

试论重叠式动词的本体性

与非重叠式动词比较 ,重叠式动词语义上动作性增强 ,语法上自足性增强 ,语用上焦点性增强 ,在语义、语法、语用三个平面上都突出了动词本身 ,体现了其本体性     

Functional calibration estimation by the maximum entropy on the mean principle

We extend the problem of obtaining an estimator for the finite population mean parameter incorporating complete auxiliary information through calibration estimation in survey sampling under a functional data framework. The functional calibration sampling weights of the estimator are obtained by matching the calibration estimation problem with the maximum entropy on the mean – MEM – principle. In particular, the calibration estimation is viewed as an infinite-dimensional linear inverse problem following the structure of the MEM approach. We give a precise theoretical setting and estimate the functional calibration weights assuming, as prior measures, the centred Gaussian and compound Poisson random measures. Additionally, through a simple simulation study, we show that the proposed functional calibration estimator improves its accuracy compared with the Horvitz–Thompson one.     

附随义务与合同对第三人的保护效力

通过附随义务理论的发展,实现合同责任主观范围或客观范围的扩张,乃是合同法实现现代社会化发展的一个显著特征。德国“附保护第三人作用的合同”就是以附随义务为媒介,将第三人纳入合同责任的保护之下,是合同责任主观范围扩张的典型制度。其法理基础在于,诚信原则要求合同债务人对与债权人有密切关系的特定第三人应负必要的照顾、保护等附随义务。通过附随义务扩大合同责任,体现了在现代社会中信赖关系的增强以及法律对信赖利益的日益重视,是合同法适应现代社会发展的一大趋势。     

A NOTE ON VARIANCE ESTIMATION FOR THE GENERALIZED REGRESSION PREDICTOR

The generalized regression (GREG) predictor is used for estimating a finite population total when the study variable is well‐related to the auxiliary variable. In 1997, Chaudhuri & Roy provided an optimal estimator for the variance of the GREG predictor within a class of non‐homogeneous quadratic estimators (H) under a certain superpopulation model M. They also found an inequality concerning the expected variances of the estimators of the variance of the GREG predictor belonging to the class H under the model M. This paper shows that the derivation of the optimal estimator and relevant inequality, presented by Chaudhuri & Roy, are incorrect.     

汉语视觉行为动词语法化分析

视觉行为动词是对人类视觉行为的状态、过程和结果等进行描述的动词。视觉行为动词的语法化具有渐变性,在词义的"虚化"程度上存在着差别。语法化现象比较典型的是"看""见""望""相"四个。通过比较分析发现,由于语义特征方面的不同,它们在语法化的动因和过程中均存在一定差异。     

SAMPLING AND ESTIMATION IN THE PRESENCE OF CUT-OFF SAMPLING

Cut-off sampling consists of deliberately excluding a set of units from possible selection in a sample, for example if the contribution of the excluded units to the total is small or if the inclusion of these units in the sample involves high costs. If the characteristics of interest of the excluded units differ from those of the rest of the population, the use of naïve estimators may result in highly biased estimates. In this paper, we discuss the use of auxiliary information to reduce the bias by means of calibration and balanced sampling. We show that the use of the available auxiliary information related to both the variable of interest and the probability of being excluded enables us to reduce the potential bias. A short numerical study supports our findings.