Predictive Inference for Big,Spatial, Non‐Gaussian Data: MODIS Cloud Data and its Change‐of‐Support

Remote sensing of the earth with satellites yields datasets that can be massive in size, nonstationary in space, and non‐Gaussian in distribution. To overcome computational challenges, we use the reduced‐rank spatial random effects (SRE) model in a statistical analysis of cloud‐mask data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on board NASA's Terra satellite. Parameterisations of cloud processes are the biggest source of uncertainty and sensitivity in different climate models’ future projections of Earth's climate. An accurate quantification of the spatial distribution of clouds, as well as a rigorously estimated pixel‐scale clear‐sky‐probability process, is needed to establish reliable estimates of cloud‐distributional changes and trends caused by climate change. Here we give a hierarchical spatial‐statistical modelling approach for a very large spatial dataset of 2.75 million pixels, corresponding to a granule of MODIS cloud‐mask data, and we use spatial change‐of‐Support relationships to estimate cloud fraction at coarser resolutions. Our model is non‐Gaussian; it postulates a hidden process for the clear‐sky probability that makes use of the SRE model, EM‐estimation, and optimal (empirical Bayes) spatial prediction of the clear‐sky‐probability process. Measures of prediction uncertainty are also given.     

基于文献关键词统计分析的我国开放与远程教育研究现状探析

以中国知网（CNKI）为平台,利用共词分析方法,对2006年1月至2015年6月间公开发表在开放与远程教育领域期刊论文的关键词进行统计分析,结合SATI软件和UCINET软件进行数据处理,探讨高频关键词之间的内在联系,揭示我国开放与远程教育研究的主题结构和核心领域。结果表明：此间我国开放与远程教育领域主要存在七大研究主题;远程学习、网络课程、学习支持服务、学习者是该领域的研究核心;移动学习、内容分析、学习科学和远程学习者将成为未来的研究热点。     

熟人社会的空间秩序

村落空间是村落历史的沉淀。不同于熟人社会研究的关系取向,文章引入空间生产的视角,基于南方村落的空间图式阐释熟人社会的空间秩序。“祠堂-阳宅”的平面空间图式定义了农民自然生命升华为道德生命的日常生活路径,而“庙宇-阴宅”的纵向空间图式定义了农民应对日常生活断裂的宗教生活模式。风水的空间实践镶嵌于村落空间图式,并促进了村落空间的结构化和立体化,而村落空间结构维系了村落熟人社会的公共性。可见,熟人社会的空间秩序是空间结构生产与社会秩序生产的统一。现代性力量逐渐抽离了村落空间的历史底蕴,释放了空间权利意识,导致村落空间结构破裂与熟人社会秩序紊乱。立足村庄社会的空间治理是突破村庄空间利益困局,实现乡村振兴的重要方式。     

产业集群成长和升级的制度经济学研究

结合生命周期理论,从制度经济学的角度出发对产业集群的制度成因、产业集群发展和成熟的制度绩效、产业集群的制度风险和产业集群升级的制度创新等进行深入的剖析,得出结论:要使产业集群保持长久的生命力,构建集群制度创新系统是十分重要的。     

Practical Maximum Pseudolikelihood for Spatial Point Patterns(with Discussion)

This paper describes a technique for computing approximate maximum pseudolikelihood estimates of the parameters of a spatial point process. The method is an extension of Berman & Turner's (1992) device for maximizing the likelihoods of inhomogeneous spatial Poisson processes. For a very wide class of spatial point process models the likelihood is intractable, while the pseudolikelihood is known explicitly, except for the computation of an integral over the sampling region. Approximation of this integral by a finite sum in a special way yields an approximate pseudolikelihood which is formally equivalent to the (weighted) likelihood of a loglinear model with Poisson responses. This can be maximized using standard statistical software for generalized linear or additive models, provided the conditional intensity of the process takes an 'exponential family' form. Using this approach a wide variety of spatial point process models of Gibbs type can be fitted rapidly, incorporating spatial trends, interaction between points, dependence on spatial covariates, and mark information.     

A general central limit theorem and a subsampling variance estimator for α‐mixing point processes

We establish a central limit theorem for multivariate summary statistics of nonstationary α‐mixing spatial point processes and a subsampling estimator of the covariance matrix of such statistics. The central limit theorem is crucial for establishing asymptotic properties of estimators in statistics for spatial point processes. The covariance matrix subsampling estimator is flexible and model free. It is needed, for example, to construct confidence intervals and ellipsoids based on asymptotic normality of estimators. We also provide a simulation study investigating an application of our results to estimating functions.     

On Bartlett correction of empirical likelihood for regularly spaced spatial data

Bartlett correction constitutes one of the attractive features of empirical likelihood because it enables the construction of confidence regions for parameters with improved coverage probabilities. We study the Bartlett correction of spatial frequency domain empirical likelihood (SFDEL) based on general spectral estimating functions for regularly spaced spatial data. This general formulation can be applied to testing and estimation problems in spatial analysis, for example testing covariance isotropy, testing covariance separability as well as estimating the parameters of spatial covariance models. We show that the SFDEL is Bartlett correctable. In particular, the improvement in coverage accuracies of the Bartlett‐corrected confidence regions depends on the underlying spatial structures. The Canadian Journal of Statistics 47: 455–472; 2019 © 2019 Statistical Society of Canada     

Development of an Asset Value Map for Disaster Risk Assessment in China by Spatial Disaggregation Using Ancillary Remote Sensing Data

The extent of economic losses due to a natural hazard and disaster depends largely on the spatial distribution of asset values in relation to the hazard intensity distribution within the affected area. Given that statistical data on asset value are collected by administrative units in China, generating spatially explicit asset exposure maps remains a key challenge for rapid postdisaster economic loss assessment. The goal of this study is to introduce a top‐down (or downscaling) approach to disaggregate administrative‐unit level asset value to grid‐cell level. To do so, finding the highly correlated “surrogate” indicators is the key. A combination of three data sets—nighttime light grid, LandScan population grid, and road density grid, is used as ancillary asset density distribution information for spatializing the asset value. As a result, a high spatial resolution asset value map of China for 2015 is generated. The spatial data set contains aggregated economic value at risk at 30 arc‐second spatial resolution. Accuracy of the spatial disaggregation reflects redistribution errors introduced by the disaggregation process as well as errors from the original ancillary data sets. The overall accuracy of the results proves to be promising. The example of using the developed disaggregated asset value map in exposure assessment of watersheds demonstrates that the data set offers immense analytical flexibility for overlay analysis according to the hazard extent. This product will help current efforts to analyze spatial characteristics of exposure and to uncover the contributions of both physical and social drivers of natural hazard and disaster across space and time.     

金融集聚、生产率增长与城乡收入差距的实证分析——基于动态空间面板模型

本文利用中国2003-2013年285个地级及以上城市的统计数据,采用动态空间面板模型实证分析了金融集聚对城市总体生产率增长及其内部城乡收入差距的影响,研究结论表明：金融集聚是促进城市总体生产率增长的重要推动力,同时也是导致城市内部城乡收入差距扩大的关键因素,这主要是因为金融集聚显著推动了城市居民人均收入水平的提高,而对农村居民人均收入水平的提升作用不显著。本文的政策含义在于,在城市金融集聚的扩散阶段还没有到来之前,政府旨在缓解城乡收入差距的金融政策可能会抑制城市总体生产率增长。     

基于灰色聚类的企业伦理能力评价研究

分析了企业伦理能力测度理论现状,提出了企业伦理能力评价指标体系。运用灰色聚类理论建立了相应的企业伦理能力评价模型,并运用该模型对海尔集团企业伦理现状进行了定量分析。