Alternative mean-squared error estimators for synthetic estimators of domain means

In forest management surveys, the mean of a variable of interest (Y) in a population composed of N equal area spatial compact elements is increasingly estimated from a model linking Y to an auxiliary vector X known for all elements in the population. It is also desired to have synthetic estimates of the mean of Y in spatially compact domains (forest stands) with no or at most one sample-based observation of Y. We develop three alternative estimators of mean-squared errors (MSE) that reduce the risk of a serious underestimation of the uncertainty in a synthetic estimate of a domain mean in cases where the employed model does not accounts for domain effects nor spatial autocorrelation in unobserved residual errors. Expansions of the estimators including anticipated effects of a spatial autocorrelation in residual errors are also provided. Simulation results indicate that the conventional model-dependent (MD) population-level estimator of variance in a synthetic estimate of a domain mean underestimates uncertainty by a wide margin. Our alternative estimators mitigated, in settings with weak to moderate domain effects and relatively small sample sizes, to a large extent, the problem of underestimating uncertainty. We demonstrate applications with examples from two actual forest inventories.     

Modelling the location decisions of manufacturing firms with a spatial point process approach

The paper is devoted to explore how the increasing availability of spatial micro-data, jointly with the diffusion of GIS software, allows to exploit micro-econometric methods based on stochastic spatial point processes in order to understand the factors that may influence the location decisions of new firms. By using the knowledge of the geographical coordinates of the newborn firms, their spatial distribution is treated as a realization of an inhomogeneous marked point process in the continuous space and the effect of spatial-varying factors on the location decisions is evaluated by parametrically modelling the intensity of the process. The study is motivated by the real issue of analysing the birth process of small and medium manufacturing firms in Tuscany, an Italian region, and it shows that the location choices of the new Tuscan firms is influenced on the one hand by the availability of infrastructures and the level of accessibility, and on the other by the presence and the characteristics of the existing firms. Moreover, the effect of these factors varies with the size and the level of technology of the new firms. Besides the specific Tuscan result, the study shows the potentiality of the described micro-econometric approach for the analysis of the spatial dynamics of firms.     

产业转移的微观引导机制：一个包含市场和政策双重因素空间经济模型

将产业承接地对迁入企业的政策支持变量引入Krugman“中心——外围”模型,分析了政府政策影响产业转移的微观机理,并进一步推理出为有效引导产业转移,承接地政府需要给予企业政策制度支持的临界条件。研究表明,在保持政策支持力度不变的情况下,当运输成本足够低时,才会促动产业空间迁移。同时,产业转移的政策支持因子的临界值随冰山运输成本的降低而先降低后增加,表明所需的政策支持力度由强趋弱;而在规模经济很大或者制造业占经济份额比例较大时,承接地政府需要对企业给予更大的政策支持力度。     

上海市居民长三角区域游的空间网络研究 ——基于旅行社推荐线路

通过选取部分上海市代表性旅行社网站以及途牛旅行网的2500条上海居民在长三角区域内的旅游线路,利用社会网络理论和方法,构建区域旅游空间网络评价指标体系,对上海居民在长三角区域内的空间网络结构进行研究.结果显示:圈层结构和距离衰减规律仍然是基础;出游时间不同,表现有差异;交通状况和资源品质对出游影响大,出游时间在3日左右表现最强.整体上,上海市居民长三角区内游在符合距离衰减规律的同时,受资源、交通等因素的影响而呈现复杂网络的特征.     

北京市轨道交通网络化发展问题及对策研究--基于职住分离的背景

轨道交通网络化发展对北京职住分离的改善及城市空间结构向多中心转变具有重要意义。当前北京轨道交通网络功能层级缺失,尚未适应现有职住空间格局;覆盖范围有限、空间形态不合理,无法有效引导城市空间结构优化;市郊线路规划为非贯穿式放射形态,远期将加剧职住空间失配;融资结构单一,无法支撑未来大规模网络化建设。因此,应完善轨道交通网络功能层级、基于远景规划审慎扩大网络范围、优化市郊线路空间布局、加强新城局域级网络及综合枢纽建设、实现多层次融资体系构建及物业联合开发。     

1644—1855年间黄河决溢的时空分布规律初探

历史时期,黄河下游决溢泛滥造成的灾害影响巨大。清代黄河河工体系建立以后,黄河下游河道两岸的河防工程逐步完善,两岸河防工程对河道的控制作用非常明显。将黄河决溢位置与河防堤段联系在一起,在数量统计的基础上利用核密度分析方法研究决溢地点的时空分布过程,可以发现在1644—1855年间黄河下游河段决溢位置存在两次由上游向下游移动的变化。综合分析这一规律,黄河在自然河道被人工堤岸约束之后,河道边界处受到河防工程的显著影响;河道内的河流发育过程仍然遵循自然的规律,于是决溢位置的核心分布区在时空分布上呈现一定的规律性。     

中国农业产业化龙头企业空间分布特征及其影响因素

农业产业化龙头企业的空间布局和集聚程度是表征一个国家农业现代化进程的重要指标。利用核密度和局部热点分析法探究中国农业产业化龙头企业的空间分布特征,并通过多元线性回归分析影响农业龙头企业空间集聚的因素。研究发现,中国农业产业龙头企业主要集中分布在中国东部的发达城市并在东部地区形成热点区,且有以这些城市为中心向周围扩散、形成区域集聚的趋势,而西部地区相对是冷点区;影响农业龙头企业发展主要因素有农业机械总动力、公路里程、铁路营运里程、司法文明指数和市场化指数;农作物播种面积及农林牧渔业固定资产投资的增加和中国农业产业化龙头企业的生长呈负相关。 研究结果揭示了中国农业产业化龙头企业的空间分布特征和变化规律,以及国家政策层面上造成中国农业产业化龙头企业区域差异化发展的原因,为完善农业产业政策体系及推进中国农业产业化进程和空间布局提出了建议。     

历史文化名城保护与古代风水意象

风水在中国古代城市的选址、营建方面有着重要影响,风水意象成为中国古代城市的显著特色之一。在今日的历史文化名城保护中,要求对历史的发展有一个准确、全面的反映。本文对古代风水文化、风水意象对古代城市的影响及如何保护城市的历史文化脉络作了一些探讨。     

Estimating the Prediction Mean Squared Error in Gaussian Stochastic Processes with Exponential Correlation Structure

Given one or more realizations from the finite dimensional marginal distribution of a stochastic process, we consider the problem of estimating the squared prediction error when predicting the process at unobserved locations. An approximation taking into account the additional variability due to estimating parameters involved in the correlation structure was developed by Kackar & Harville (1984) and was revisited by Harville & Jeske (1992) as well as Zimmerman & Cressie (1992). The present paper discusses an extension of these methods. The approaches will be compared via an extensive simulation study for models with and without random error term. Effects due to the designs used for prediction and for model fitting as well as due to the strength of the correlation between neighbouring observations of the stochastic process are investigated. The results show that considering the additional variability in the predictor due to estimating the covariance structure is of great importance and should not be neglected in practical applications.