Approximating hidden Gaussian Markov random fields

Summary.  Gaussian Markov random-field (GMRF) models are frequently used in a wide variety of applications. In most cases parts of the GMRF are observed through mutually independent data; hence the full conditional of the GMRF, a hidden GMRF (HGMRF), is of interest. We are concerned with the case where the likelihood is non-Gaussian, leading to non-Gaussian HGMRF models. Several researchers have constructed block sampling Markov chain Monte Carlo schemes based on approximations of the HGMRF by a GMRF, using a second-order expansion of the log-density at or near the mode. This is possible as the GMRF approximation can be sampled exactly with a known normalizing constant. The Markov property of the GMRF approximation yields computational efficiency.The main contribution in the paper is to go beyond the GMRF approximation and to construct a class of non-Gaussian approximations which adapt automatically to the particular HGMRF that is under study. The accuracy can be tuned by intuitive parameters to nearly any precision. These non-Gaussian approximations share the same computational complexity as those which are based on GMRFs and can be sampled exactly with computable normalizing constants. We apply our approximations in spatial disease mapping and model-based geostatistical models with different likelihoods, obtain procedures for block updating and construct Metropolized independence samplers.     

Data depth and correlation

Summary: We describe depth–based graphical displays that show the interdependence of multivariate distributions. The plots involve one–dimensional curves or bivariate scatterplots, so they are easier to interpret than correlation matrices. The correlation curve, modelled on the scale curve of Liu et al. (1999), compares the volume of the observed central regions with the volume under independence. The correlation DD–plot is the scatterplot of depth values under a reference distribution against depth values under independence. The area of the plot gives a measure of distance from independence. Correlation curve and DD-plot require an independence model as a baseline: Besides classical parametric specifications, a nonparametric estimator, derived from the randomization principle, is used. Combining data depth and the notion of quadrant dependence, quadrant correlation trajectories are obtained which allow simultaneous representation of subsets of variables. The properties of the plots for the multivariate normal distribution are investigated. Some real data examples are illustrated. *This work was completed with the support of Ca Foscari University.     

关于Feigenbaum型泛函方程的C^1解

利用Schauder不动点定理、自同胚和紧凸子集的相关性质研究Feigenbaum型泛函方程的连续可微解的存在性和唯一性.     

企业型社区转型的组织嵌入与路径依赖

我国社区转型的类型是多样化的,企业型社区兼有单位科层制传统、盈利性组织双重特点。社区建设的目标受企业型社区组织的路径依赖所制约。基于此类社区的嵌入性架构,企业型社区嵌入企业组织中,形成多层次路径依赖,分别表现在资源的依赖性、组织制度的同构、双重嵌入性等多个维度,社区与企业之间形成的规制型和文化——规范型两类制度关系,共同构成了对社区建设的利弊影响。     

外场操控的原子与分子碰撞

对原子与分子碰撞研究的历史进行了简单的回顾,特别是对近几十年来外场下的原子与分子碰撞研究进行了综述,并对原子与分子碰撞的外场操控研究前景进行了展望.     

弯曲液面的临界光反射现象

实验中发现了弯曲液面的临界光反射现象,并采集到清晰的、对比度高的弯曲液面临界反射图样。在激光束斜入射的情况下,弯曲液面临界反射的图样中,有一椭圆状暗场,暗场附近区域有明亮清晰的条纹。根据几何光学的分析,解释了这一临界光反射现象。     

巴洛克文学的多元文化价值及其影响场域

巴洛克文学曾受到文学批评史的不公正对待已是不争的事实。可是文学史的发展轨迹最终表明巴洛克文学具有多元文化价值、强大的生命力和不容忽视的影响场域。巴洛克文学的多元文化价值表现在：其一,生动再现17世纪欧洲各国的社会生活现实;其二,体现多元化的审美文化追求。巴洛克文学的影响场域表现为后世作家对其思想和艺术手法的借鉴、移植和化用,虽然亦存在着难以融合的断裂感和新异感。另外,这种影响还体现为一种追新逐异、兼收并蓄的＂巴洛克精神＂的广泛渗透。     

流动相似律在气流式倾角传感器中的应用

气流式惯性传感器因其独特的优点引起大家的关注,但是环境温度不可避免地对气流式传感器性能有影响,会产生严重的温度漂移。它不仅局限了传感器的应用范围,而且还影响了传感器性能的进一步提高。本文通过数值模拟的方法,研究了环境温度变化时气流式倾角传感器腔体内的流场变化,分析了流场变化对传感器性能的影响机理,并利用相似理论讨论了一种新的消除环境温度影响的解决办法。结果表明,可以通过设计的补偿电路改变热源温度使流场保持相似来消除环境温度的影响。     

强吹除雪气固两相流流场数值模拟分析

为研究和分析机场强吹除雪气固两相流流场的压力、速度和雪粒运移规律,依据离散粒子模型建立了强吹除雪气固两相流方程,并采用计算流体力学数值分析方法,对机场强吹除雪的气固两相流流场进行数值模拟分析,得到了气固两相流流场的压力、速度分布曲线和不同时刻下的雪粒分布规律．数值分析结果表明,气固两相流场发展过程迅速,速度分布符合射流理论,湍流强度变化剧烈．数值模拟得到强风强吹除雪的吹雪时间为2．5s．     

探析李安导演的影像表达与意境营造

著名华裔电影导演李安博采东西方之所长,用影像编织了一个独特的艺术领域。他在文本核心执着于戏剧性元素的追求,选择了一种静水流深、独具魅力的镜头语言,同时在意境营造中,以影像写诗,追求诗意的凝聚。