DENSITY ESTIMATION FOR CLUSTERED DATA

The commonly used survey technique of clustering introduces dependence into sample data. Such data is frequently used in economic analysis, though the dependence induced by the sample structure of the data is often ignored. In this paper, the effect of clustering on the non-parametric, kernel estimate of the density, f(x), is examined. The window width commonly used for density estimation for the case of i.i.d. data is shown to no longer be optimal. A new optimal bandwidth using a higher-order kernel is proposed and is shown to give a smaller integrated mean squared error than two window widths which are widely used for the case of i.i.d. data. Several illustrations from simulation are provided.     

The cluster that never was: germ warfare experiments and health authority reality in Dorset

In 1997 intense media coverage raised public concerns about germ warfare simulation experiments conducted by the Ministry of Defence during the 1960s, which included the release of bacteria over Dorset. Families in East Lulworth, Dorset, have linked this with allegedly high rates of miscarriages, still-births, congenital malformations, learning and other neurodevelopmental disabilities in their village. The response of the Dorset Health Authority (DHA) included the examination of background information from the Ministry of Defence, national data on congenital malformations in Dorset, health information collected by campaigners and a systematic health survey conducted by the DHA among former and current residents of East Lulworth. The investigation did not confirm the presence of a cluster. It is debatable whether the DHA should have proceeded with their survey when none of the other more immediately available results indicated the presence of a cluster.     

建立中国(上海)自由贸易试验区动因及其经济效应分析

上海自贸试验区的建立,不是着眼于一城市、一区域的发展,而是力图通过开放转变政府角色、推动制度创新,突破金融领域的改革难点,从而带来"制度红利",充分运用市场调配资源的高效为我国社会主义建设事业服务。上海要实现建成金融中心、贸易中心的宏伟目标,必须从自贸试验区开始,从根本上摒除要素流动的障碍,协调好与经济腹地,与香港、深圳前海等区域的关系,实现区域经济协同发展。上海自贸试验区的建成,必将进一步推动上海服务业产业集聚,推动上海金融中心、航运中心、贸易中心更上一个能级,辐射长江流域甚至更广阔的地域。     

一种货运需求预测的灰色系统模型

本文以上海市货运量、货运周转量的时间序列为依据,应用灰色系统模型(Grey Dynamic Model),建立了货运中长期预测模型,并提出了至2000年的预测值。经测试,1989年的预测值与实际值相比较,吻合度高达95%以上。     

“闪动簇团”与水反常膨胀

本文介绍了液态水结构的“闪动簇团”理论,运用该理论能很好地解释液态水的反常热膨胀问题.     

蓝黄九市经济-生态-社会的协调发展

通过以蓝黄九市2005—2014的面板数据为基础,运用协同学理论构建蓝黄九市经济-生态-社会协调发展模型,分析蓝黄九市三系统的发展现状及演化过程可以看出,经济、生态、社会三系统之间具有较强的互补作用。2014年青岛市耦合协调度水平最高,德州市最低。除青岛市达到优质协调外,其余城市的协调类型为:日照市、潍坊市、滨州市、淄博市、德州市属经济发展相对滞后型;烟台市属生态发展相对滞后型;威海市、东营市属社会发展相对滞后型。经济系统关键影响因子是GDP等,生态系统关键影响因子是污水集中处理率等,社会系统关键影响因子是公用设施投资等。     

空间溢出视角下的生产性服务业集聚与长三角城市群经济增长效率

本文利用空间杜宾模型实证研究了生产性服务业集聚对长三角城市群经济增长效率的影响及空间溢出效应。结果表明,生产性服务业集聚不仅能够显著提升本地区的经济增长效率,还对邻近城市具有正向的空间溢出效应,但这种影响在生产性服务业的细分行业之间存在一定异质性。进一步分析发现,生产性服务业集聚的MAR外部性和Jacobs外部性都有利于长三角城市群经济增长效率的提升,而Porter 外部性对经济增长效率具有负面影响。在空间溢出效应方面,Jacobs外部性对经济发展水平相近的城市具有负向溢出效应,Porter外部性对人力资本水平相近的城市具有正向溢出效应。此外,生产性服务业与制造业协同集聚对本地区和人力资本水平相近城市的经济增长效率具有显著促进作用,但对邻近城市和经济发展水平相近城市的经济增长效率因“虹吸效应”而产生一定的抑制作用。这些研究,对如何更有针对性地加快提升长三角城市群经济增长效率,提供了有价值的理论依据。     

Conditional Gaussian mixture modelling for dietary pattern analysis

Summary.  Free-living individuals have multifaceted diets and consume foods in numerous combinations. In epidemiological studies it is desirable to characterize individual diets not only in terms of the quantity of individual dietary components but also in terms of dietary patterns. We describe the conditional Gaussian mixture model for dietary pattern analysis and show how it can be adapted to take account of important characteristics of self-reported dietary data. We illustrate this approach with an analysis of the 2000–2001 National Diet and Nutrition Survey of adults. The results strongly favoured a mixture model solution allowing clusters to vary in shape and size, over the standard approach that has been used previously to find dietary patterns.     

供应链合作伙伴的分类及评价研究

文章在提出供应链合作伙伴二阶段模型的基础上,将多元统计方法中的聚类分析和系统工程中的密切值法综合应用于供应链合作伙伴第一阶段选择中：通过聚类方法将潜在的合作伙伴划分群体,再应用密切值法对聚类分析所得到的群体进行优先次序的排序和等级的划分,得出优先群体,供核心企业参考,以提高企业选择合作伙伴的效率并减少其选择成本。     

Clustering via nonparametric density estimation

Although Hartigan (1975) had already put forward the idea of connecting identification of subpopulations with regions with high density of the underlying probability distribution, the actual development of methods for cluster analysis has largely shifted towards other directions, for computational convenience. Current computational resources allow us to reconsider this formulation and to develop clustering techniques directly in order to identify local modes of the density. Given a set of observations, a nonparametric estimate of the underlying density function is constructed, and subsets of points with high density are formed through suitable manipulation of the associated Delaunay triangulation. The method is illustrated with some numerical examples.