SPECIAL ISSUE： REGIONAL CONVERGENCE AND COORDINATED URBAN GROWTH Regional Correlation and Spatial Spillovers in China＇s Regional Economic Growth

本文使用探索性空间数据分析工具研究了1988．2009年问中国各省区人均GDP的空间分布格局与特征,结果显示,一方面,存在着全域范围的正的空间自相关性,并且这种相关性随着时间的推移在增大;另一方面,局域相关也显示出中国局域性的空间集聚特征越来越明显。以一个表征市场潜能对地区经济发展影响的新经济地理学模型为基础,本文通过计量分析进一步考察了中国区域经济发展的空间溢出效应。经验分析表明,空间溢出效应是中国地区经济发展不可忽视的重要影响因素,市场潜能每增长1％,地区人均GDP增长率将提高0．47％,超过了地区固定资产投资增长的弹性值。当然,实证分析也发现这种空间溢出效应会随着地区间距离间隔的增加而减少。     

农地承包权置换城镇社保的空间计量分析

通过对江西、安徽、江苏三省42个乡镇样本农户的实地调查数据,分析了农户在农地承包权置换城镇社保意愿选择方面的影响因素,得出乡镇家庭人均纯收入、乡镇所有农户医疗和养老支出占总收入比重的平均值、乡镇所有家庭务工比率的平均值、城镇人均社保缴纳的费用对农户选择农地承包权置换城镇社保的意愿存在显著影响。同时采用空间自相关的莫兰指数来反映不同地区之间农户选择农地承包权置换城镇社保意愿的空间分布模式,验证农户在选择农地承包权置换城镇社保的意愿上存在相互影响的特征。     

Household solid fuel use in the Philippines: an exploratory spatial and social analysis

Over two billion people use solid fuels for basic needs such as cooking, with consequences for the environment, human health, and social and economic development. In the Philippines, 65% of households use solid fuels for cooking. To better understand this phenomenon, this study uses spatial analysis and multilevel modeling to answer: (1) Are there spatial differences in solid fuel use for cooking in the Philippines? (2) What social characteristics are associated with such use? The study finds that both types of characteristics are significantly related to solid fuel use. Implications for social work policy, practice, and research are discussed.     

The variability of rainfall acidity revisited

Six years of rainfall-event pH measurements from the nine-station MAP3S/PCN monitoring network in the eastern United States were analyzed. The initial objective was an attempted validation of the model developed by Eynon and Switzer (1983, Canad. J. Statist. 11, 11–24) on this independent data set. Because some features of the structure presumed in the model are not evident in this data set, the underlying structure of the data was then explored in some detail. Both aspects of the investigation confirmed that the identification of an appropriate statistical model for such data is a difficult undertaking; anticipated structure may not be evident, and the data corresponding to specific stations or years may exhibit anomalous behavior.     

依附于外部环境的公共艺术设计

公共艺术设计对组成城市外部景观环境、弥补因工业化而造成的建筑环境及其环境界面的缺陷起着十分重要的作用。依附于城市外部环境场所的公共艺术设计的支撑点 ,主要取决于三大因素———功能性因素、结构性因素、场所性因素     

ALLOCATION OF REMOTELY SENSED DATA USING MARKOV MODELS FOR IMAGE DATA AND PIXEL LABELS

For remotely sensed data, this paper reviews the Bayesian approach to the allocation of picture elements (pixels) to groups. Group labels are assumed a priori to be spatially correlated and, conditional on the labels, the image data are also assumed to be spatially correlated. The models considered have the property that the posterior distribution of the pixel labels given the image data inherits conditional independence constraints. Two allocation algorithms which exploit this fad are discussed. These algorithms are based on maximising the posterior distribution, and involve the use of neighbouring image and label data to update the label of any given pixel. The effect of spatial correlation in the image data on allocation performance is examined.     

地缘政治学的性质：人-境关系的视角

环境决定论和可能论是地理学思想史中最具概括性的两大传统,也是贯穿了整个地理学和地缘政治学争论的一条主线.决定论和可能论争论的焦点在于两者对人-境关系的中介区域,即文化、技术和社会组织的框架内人的自由意志的态度.对文化和社会生活的关注因而也成为地理学家的研究主题.地缘政治学就在这种人文倾向中发展为一种国际政治的空间分析方法.地缘政治学是描述和解释国际政治的空间差异的科学.它关注事件的空间进程的同时,也不放过事件的时间进程.     

Semiparametric Proportional Odds Models for Spatially Correlated Survival Data

The last decade has witnessed major developments in Geographical Information Systems (GIS) technology resulting in the need for statisticians to develop models that account for spatial clustering and variation. In public health settings, epidemiologists and health-care professionals are interested in discerning spatial patterns in survival data that might exist among the counties. This paper develops a Bayesian hierarchical model for capturing spatial heterogeneity within the framework of proportional odds. This is deemed more appropriate when a substantial percentage of subjects enjoy prolonged survival. We discuss the implementation issues of our models, perform comparisons among competing models and illustrate with data from the SEER (Surveillance Epidemiology and End Results) database of the National Cancer Institute, paying particular attention to the underlying spatial story.     

Including structural measurement errors in the nonlinear regression analysis of clustered data

This paper extends methods for nonlinear regression analysis that have developed for the analysis of clustered data. Its novelty lies in its dual incorporation of random cluster effects and structural error in the measurement of the explanatory variables. Moments up to second order are assumed to have been specified for the latter to enable a generalized estimating equations approach to be used for fitting and testing nonlinear models linking response to these explanatory variables and random effects. Taylor expansion methods are used, and a difficulty with earlier approaches overcome. Finally we describe an application of this methodology to indicate how it can be used. That application concerns the degree of association of hospital admissions for acute respiratory health problems and air pollution.     

Local Adaptivity of Kernel Estimates with Plug-in Local Bandwidth Selectors

In non-parametric function estimation selection of a smoothing parameter is one of the most important issues. The performance of smoothing techniques depends highly on the choice of this parameter. Preferably the bandwidth should be determined via a data-driven procedure. In this paper we consider kernel estimators in a white noise model, and investigate whether locally adaptive plug-in bandwidths can achieve optimal global rates of convergence. We consider various classes of functions: Sobolev classes, bounded variation function classes, classes of convex functions and classes of monotone functions. We study the situations of pilot estimation with oversmoothing and without oversmoothing. Our main finding is that simple local plug-in bandwidth selectors can adapt to spatial inhomogeneity of the regression function as long as there are no local oscillations of high frequency. We establish the pointwise asymptotic distribution of the regression estimator with local plug-in bandwidth.