A spatiotemporal analysis of public pharmaceutical expenditure

A regression model for per capita public pharmaceutical expenditure, based on aggregate data from fifty Spanish provinces, observed annually for the period 1996–2002 is analyzed. The necessity of simultaneously controlling for dynamic patterns and spatial autocorrelation is demonstrated. As the aim of the present and related studies of small-area variation is to control for spatial association rather than to formulate it as an explicit part of a model, the traditional application of parametric spatial autocorrelation or spatial autoregression specifications seems unnecessarily restrictive and superfluous. The present study analyzes the effects of spatial association using a non-parametric spatial filtering approach. The importance of adjusting for spatial association is confirmed, but it is further shown that the parametric and the non-parametric approaches may lead to substantially different conclusions regarding explanation of pharmaceutical expenditure variations. Thus, the need for further evidence on the implications of spatial association—and the recognition that this is more than just spatial autocorrelation and/or spatial autoregression—when analyzing complex large area behavior using small area data is demonstrated.     

Time,space and hedonic prediction accuracy: evidence from Corsican apartment markets

In this study, we propose a hedonic housing model to address spatial and temporal latent structures simultaneously. With the development of spatial econometrics and spatial statistics, economists can now better assess the impact of spatial correlation on house prices. However, the simultaneous handling of spatial and temporal correlation is still under development. Since the commonly used spatial econometric models cannot appropriately account for the two kinds of correlation simultaneously, we propose using a hierarchical spatiotemporal model from spatial statistics. Based on a Bayesian framework and a Stochastic Partial Differential Equation approach, estimation is carried out via Integrated Nested Laplace Approximations. We then perform an empirical study on apartment transaction prices in Corsica (France) using the proposed model. The empirical results demonstrate that the prediction performance of the hierarchical spatiotemporal model is the best among all candidate models. Moreover, the hedonic estimates are affected by spatial effects and temporal effects. Ignoring these effects could result in serious forecasting issues.     

The enhancement of spatial microsimulation models using geodemographics

The generation of synthetic population estimates through spatial microsimulation has been a popular technique in recent years, with applications to research and policy problems in many areas of social science. Estimation techniques typically involve cloning or matching households in surveys with small-area census data. When model estimates are benchmarked against real-world data, the models are typically well behaved and very robust, but they can struggle to capture the diversity of spatial variations shown by observed data. We argue in this paper that this is the result of 3 potential problems in spatial microsimulation estimation techniques. The first issue results from the matching process in the estimation techniques, and the second problem relates to the variations of household types in the surveys being reweighted. Third, similar household types may show different behaviours or have different attributes depending on geographical factors not contained in surveys (such as the proximity of service or job locations). The aim of this paper is to demonstrate and measure the loss of accuracy and intensity induced by spatial microsimulation in the context of real individual data. It will be argued in particular that while the first two problems have begun to be addressed in the literature, the third issue is still largely unreported. The paper will thus suggest a solution framework which involves linking spatial microsimulation models with geodemographics and demonstrates the promise of this technique with real numerical experiments.     

Production technology and agglomeration for Japanese prefectures during 1991–2000*

We analyse the seemingly unrelated regression (SUR) models with spatial dependencies from a Bayesian point of view and estimate the parameters of the models using a Markov chain Monte Carlo (MCMC) method. Further, we analyse the production technology and the economics of agglomeration in Japanese prefectures from 1991 to 2000, simultaneously taking into account spatial and serial correlation. Model comparison is done via log‐marginal likelihoods, and it is found that the spatial error SUR model is the best model and that the economics of agglomeration and spatial heterogeneity decreased over this decade. Resumen. Analizamos modelos de ecuaciones aparentemente no relacionadas (SUR, siglas en inglés) con dependencias espaciales desde un punto de vista bayesiano y estimamos los parámetros de los modelos utilizando el método de Monte Carlo basado en cadenas de Markov (MCMC). Además, analizamos la tecnología de la producción y las economías de aglomeración en prefecturas japonesas desde 1991 a 2000, teniendo en cuenta simultáneamente la correlación espacial y serial. La comparación de modelos se realiza mediante verosimilitud log‐marginal, y se encontró que el error espacial del modelo SUR es el mejor modelo y que las economías de aglomeración y la heterogeneidad espacial disminuyeron durante esta década.      

小面积混凝土路面拓宽技术浅析

针对混凝土路面拓宽的实际问题,对拓宽处理后容易产生的病害进行了分析,并吸取以往老路拓宽的工程经验,对于较小面积混凝土路面拓宽问题提出两种施工处理方法,并且通过对工后沉降及裂缝的观测、统计分析,对施工处理效果进行了总结,希望能对同类型工程有一定实践参考意义。     

基于单键群方法的岩石破裂声发射时空分布特征的试验研究

 基于声发射定位技术和单键群方法,对在单轴压缩条件下岩石破裂过程中的声发射空间相关长度的变化特征进行试验研究。利用单键群构架的键长分布对声发射事件进行分色,可定量确定声发射事件集中程度。研究结果表明：基于单键群方法,影响声发射空间相关长度变化的因素有2个,一是应力的释放导致空间相关长度的下降;二是应力场的转移导致空间相关长度的增长。根据声发射空间相关长度变化的不同,可将岩石岩样分为3种类型：(1) 破坏前无明显塑性变形阶段的岩石岩样,空间相关长度呈现以幂律为特征的加速增长态势,且在岩石破坏前达到最大值;(2) 对于破坏前有明显塑性变形阶段的岩石岩样,在塑性变形阶段,应力场的转移和岩石内部局部塑性2种因素的影响使得空间相关出现或增长或下降的波动现象;(3) 对于加载过程中出现明显局部裂纹的岩样,局部破裂会导致声发射事件群集,致使空间长度减小,但是对于岩石整个破坏过程,空间相关长度呈现整体的增长趋势。单键群构架的键数具有分形特征,其反映的声发射事件的空间演化特征与空间相关长度所反映的情况一致。空间相关长度的增长反映了岩石内部应力场的长程转移过程。在塑性变形阶段,空间相关长度与之前阶段变化的差异对于预测岩石的破坏具有重要意义。     

区域场地近地表速度结构建模研究

近地表速度结构是全面考虑城市区域场地地震效应,精细模拟地震动场及建筑群震害的基础.针对复杂交错沉积的区域场地,建立了先基于工程地质先验信息限定交错土体边界,利用序贯指示模拟求解各类交错土体空间概率分布,再依据剪切波速与工程地质结构的空间相关关系,借助序贯高斯模拟构建波速结构模型的方法;在搜集分析钻孔波速资料基础上,构建...     

A Simulation Model Of Economic Growth Dynamics

A small-area economic base study is carried out through computer simulation using techniques of Industrial Dynamics. The model explicitly incorporates feedback between population and employment sectors to determine population, migration, job changes, labor force, participation rate change and industrial location and growth. The authors feel the technique holds promise for policy guidance especially in light of the speed and low cost of model construction and use. They suggest a number of specific questions which the model can help to answer.     

Using Bayesian posterior model probabilities to identify omitted variables in spatial regression models

LeSage and Pace (2009) consider the impact of omitted variables in the face of spatial dependence in the disturbance process of a linear regression relationship and show that this can lead to a spatial Durbin model. Monte Carlo experiments and Bayesian model comparison methods are used to distinguish between spatial error and Durbin model specifications that arise with varying levels of correlation between included and omitted variables. The Monte Carlo results suggest use of the common factor relationship developed in Burridge (1981) as a way to test for the presence of omitted variables bias influencing specific explanatory variables.     

Optimized blasting design for large-scale quarrying based on a 3-D spatial distribution of rock factor

Rock fragmentation plays a critical role in large-scale quarrying operations because of its direct effects on the costs of drilling, blasting, secondary blasting and crushing. In this aspect, it is essential to consider rock fragmentation in blasting design. The optimum blasting pattern to excavate a quarry efficiently and economically can be determined based on the minimum production cost which is generally estimated according to rock fragmentation. By comparing various prediction models, it can be ascertained that the results obtained from the Kuz–Ram model relatively coincide with the results from field measurements. This model uses the rock factor to signify conditions of rock mass such as block size, rock jointing, strength, and others. The rock factor is estimated from geologic data such as block size of rock mass, rock jointing, strength, and others, and its 3-D spatial distribution was predicted by a sequential indicator simulation (SIS) technique. The entire quarry in question was classified into three types of rock mass and an optimum blasting pattern was proposed for each type based on the 3-D spatial distribution of the rock factor. It can, therefore, be concluded that it is possible to design a blasting pattern to achieve a minimum production cost in large-scale quarrying operations by predicting rock fragmentation based on the 3-D spatial distribution of the rock factor.     

Which persistent organic pollutants can we map in soil using a large spacing systematic soil monitoring design? A case study in Northern France

Persistent organic pollutants (POPs) impact upon human and animal health and the wider environment. It is important to determine where POPs are found and the spatial pattern of POP variation. The concentrations of 90 molecules which are members of four families of POPs and two families of herbicides were measured within a region of Northern France as part of the French National Soil Monitoring Network (RMQS: Réseau de Mesures de la Qualité des Sols). We also gather information on five covariates (elevation, soil organic carbon content, road density, land cover and population density) which might influence POP concentrations. The study region contains 105 RMQS observation sites arranged on a regular square grid with spacing of 16 km. The observations include hot-spots at sites of POP application, smaller concentrations where POPs have been dispersed and observations less than the limit of quantification (LOQ) where the soil has not been impacted by POPs. Fifty nine of the molecules were detected at less than 50 sites and hence the data were unsuitable for spatial analyses. We represent the variation of the remaining 31 molecules by various linear mixed models which can include fixed effects (i.e. linear relationships between the molecule concentrations and covariates) and spatially correlated random effects. The best model for each molecule is selected by the Akaike Information Criterion. For nine of the molecules, spatial correlation is evident and hence they can potentially be mapped. For four of these molecules, the spatial correlation cannot be wholly explained by fixed effects. It appears that these molecules have been transported away from their application sites and are now dispersed across the study region with the largest concentrations found in a heavily populated depression. More complicated statistical models and sampling designs are required to explain the distribution of the less dispersed molecules.     

Organisational motives and spatial effects in Internet adoption and intensity of use: evidence from French industrial firms

The aim of this study is to examine the reasons why firms use ICTs at varying rates, by making a distinction between the two stages of their diffusion: their adoption and the intensity of their use. What are the differences between Internet adopters (in terms of their internal organization and external environment) that explain the intensity with which they use this technology? Furthermore, do these processes vary according to the type of area in which firms are located (urban vs. rural)? A model of technological diffusion is constructed that merges two types of models: those that concentrate on epidemic effects and the so-called equilibrium models that consider the decision to adopt new technologies as a result of an economic calculation by firms. To test this model, we use data drawn from a recent French national survey of 5,200 industrial firms (“ICT and E-commerce”, 2002). One striking result of this study is that we do not obtain a significant positive correlation between firm’s size and Internet intensity of use. Moreover, though spatial disparities related to ICT adoption are no longer significant in France, they remain very important in the processes of ICT appropriation and use by firms. The results also indicate that the determinants of the intensity of Internet use vary significantly according to the firms’ location: epidemics effects play an essential role in the case of urban the firms, while rank effects are essential in low density areas.     

Expanded reliability-based design of piles in spatially variable soil using efficient Monte Carlo simulations

Inherent spatial variability is considered as a major source of uncertainties in soil properties, and it affects significantly the performance of geotechnical structures. However, research that considers, directly and explicitly, the inherent spatial variability in reliability-based design (RBD) of geotechnical structures is limited. This paper develops a RBD approach that integrates a Monte Carlo Simulation (MCS)-based RBD approach, namely the expanded RBD approach, with random field theory to model, both directly and explicitly, the inherent spatial variability of soil properties in RBD of drilled shafts. The proposed approach is implemented in a commonly-available spreadsheet environment to effectively remove the hurdle of reliability computational algorithms and to provide a user-friendly graphical user interface to practicing engineers. To improve the efficiency and resolution of MCS at small probability levels, the expanded RBD approach is enhanced with an advanced MCS method called “Subset Simulation”. Equations are derived for the integration of the expanded RBD approach and Subset Simulation. The proposed approach is illustrated through a drilled shaft design example, and is applied to explore the effects of inherent spatial variability (including the scale of fluctuation and correlation structure) and to evaluate systematically the equivalent variance technique that is commonly used to indirectly model inherent spatial variability in current RBD approaches. It is found that inherent spatial variability significantly affects the RBD of drilled shafts, and its effects are considered in RBD using the proposed approach in a direct and explicit manner. In addition, the results show that the indirect modeling of inherent spatial variability using the equivalent variance technique with the simplified form of variance reduction function in RBD might lead to relatively conservative designs in design practice.     

An analytical method for quantifying the correlation among slope failure modes in spatially variable soils

An efficient analytical method for quantifying the correlation between performance functions of different slope failure modes in spatially variable soils is proposed, and its performance in slope system reliability analysis is investigated. First, a new correlation coefficient (NCC) is proposed to evaluate the correlation among slope failure modes considering spatial variability. For comparison and verification, the simulation-based correlation coefficient (SCC) is also presented. Second, appying these two types of correlation coefficients, the effects of soil spatial variability on the representative slip surfaces (RSSs) and the system probability of slope failure are investigated using different system reliability methods, including a probabilistic network evaluation technique, a risk aggregation approach, and a bimodal bounds method. A single-layered cohesive slope is investigated to illustrate the validity of the proposed NCC. The results indicate that the proposed NCC can efficiently and accurately quantify the correlation among slope failure modes considering soil spatial variability. The number of RSSs indicated by the NCC is in good agreement with the number obtained using the SCC. The system failure probabilities of slope stability obtained with the SCC and the NCC using a risk aggregation approach are generally comparable. Also, the system reliability bounds of slope stability obtained using the NCC are relatively close together and comparable to those obtained using the SCC. Thus, the NCC shows good performance when evaluating the correlation among slope failure modes, and was effectively applied to analyze a single-layered cohesive slope considering soil spatial variability.     

Modeling particle fate in ventilation system—Part II: Case study

In this paper the particle filter group model, which was presented in the first part of this series of study, is employed to predict particle fate in a typical ventilation system. The model simultaneously takes into account the interactions between particle transport in ventilation ducts and rooms and particle spatial distribution. It has been proven that an entire ventilation system, including filters, ducts and rooms, can be regarded as a serial of filters in steady-state cases, hence the name “particle filter group model”. With this model, the particle concentration and quantity of deposited particles in each part of the ventilation system can be easily calculated.     

Spatial fixed effects and spatial dependence in a single cross‐section

We investigate the common conjecture in applied econometric work that the inclusion of spatial fixed effects in a regression specification for a single cross‐sectional data set removes spatial dependence. We demonstrate analytically and by means of a series of simulation experiments how evidence of the removal of spatial autocorrelation by spatial fixed effects may be spurious when the true data generating processes (DGP) takes the form of a spatial lag or spatial error dependence. In addition, we also show that spatial fixed effects correctly remove spatial correlation only in the special case where the dependence is group‐wise, with all observations in the same group as neighbours of each other.     

An analysis of the relationship between land use density of office buildings and urban street configuration: Case studies of two areas in Seoul by space syntax analysis

The purpose of this article is to investigate the relationship between urban street configuration and land use density of office buildings. The land use density is another criterion of land value since the land use density intends to increase according to the rising of the land value to keep up with the increasing demand of benefits in limited areas. In order to confirm the differentiation of land use pattern according to the change of urban configuration, two areas of different urban street configurations were studied. Urban street configurations of the two areas were analyzed using the Space Syntax theory. The Axman program is used to estimate integration, connectivity, control, R-3 (local integration) and intelligibility values. Based on the computation two axial maps were produced. The axial lines represent spaces for vehicular access, including pedestrian footpaths. From the spatial analysis it can be concluded that there is a fundamental difference in spatial configuration between the two areas, in terms of their local structure as well as their global context.Correlation analysis identified the relationship between the building level and the space syntax variables. In area A, global integration, connectivity and local integration had strong correlation with building level and control also had valid correlation. In area B, all variables, including control variable, had strong correlation with building level. It reveals that the urban configuration influences the physical formation of cities. This result indicates that the land use density is significantly influenced by the street configuration.     

A linked spatial and temporal model of the chemical and biological status of a large, acid-sensitive river network

Freshwater sensitivity to acidification varies according to geology, soils and land-use, and consequently it remains difficult to quantify the current extent of acidification, or its biological impacts, based on limited spot samples. The problem is particularly acute for river systems, where the transition from acid to circum-neutral conditions can occur within short distances. This paper links an established point-based long-term acidification model (MAGIC) with a landscape-based mixing model (PEARLS) to simulate spatial and temporal variations in acidification for a 256 km(2) catchment in North Wales. Empirical relationships are used to predict changes in the probability of occurrence of an indicator invertebrate species, Baetis rhodani, across the catchment as a function of changing chemical status. Results suggest that, at present, 27% of the river network has a mean acid neutralising capacity (ANC) below a biologically-relevant threshold of 20 microeq l(-1). At high flows, this proportion increases to 45%. The model suggests that only around 16% of the stream network had a mean ANC < 20 microeq l(-1) in 1850, but that this increased to 42% at the sulphur deposition peak around 1970. By 2050 recovery is predicted, but with some persistence of acid conditions in the most sensitive, peaty headwaters. Stream chemical suitability for Baetis rhodani is also expected to increase in formerly acidified areas, but for overall abundance to remain below that simulated in 1850. The approach of linking plot-scale process-based models to catchment mixing models provides a potential means of predicting the past and future spatial extent of acidification within large, heterogeneous river networks and regions. Further development of ecological response models to include other chemical predictor variables and the effects of acid episodes would allow more realistic simulation of the temporal and spatial dynamics of ecosystem recovery from acidification.     

城市公园景观感知效应动态评价方法 ——基于景观视觉与热舒适性的叠加研究

结合景观感知主体(人群)的多样性和时间动态性,将城市公园景观视觉与热舒适性叠加,构建评估模型与方法,动态评价城市公园景观感知效应。首先,选择基本视觉元素和视觉敏感度两方面共6项指标计算景观视觉空间分布;其次,基于实测校正ENVI-met模型,模拟2h间隔的生理等效温度(PET),再利用热感觉投票获得热舒适性的空间分布;最后,依据季节和早中晚时间序列,对于少年、青年和中老年3类人群,利用现场访谈与问卷调查统计,确定景观视觉与热舒适性的叠加权重,获得动态评价结果。针对中老年人群在重庆市沙坪公园进行实证分析,得出秋季的早中晚叠加评价结果与实地调查结果较为相符。该评价方法结合景观视觉和热舒适性,基于人群构成,构建了城市公园景观感知效应的时间动态评价图谱,为城市公园景观空间环境的规划设计、感知制图,以及量化测度公园的生理和心理综合感知效应研究提供了一种新思路。     

Exploring relationships between semi-variogram and spatial autoregressive models

This paper seeks to continue the building of a common foundation for spatial statistics and geostatistics. Equations from the conditional autoregressive (CAR) model of spatial statistics for estimating missing geo-referenced data have been found to be exactly those best linear unbiased estimates obtained with the exponential semi-variogram model of kriging, but in terms of the inverse covariance matrix rather than the covariance matrix itself. Further articulation of such relations, between the moving average (MA) and simultaneous autoregressive (SAR) or autoregressive response (AR) models of spatial statistics, and, respectively, the linear and Gaussian semi-variogram models of kriging, is outlined. The exploratory graphical and numerical work summarized in this paper indicates the following: (a) there is evidence to pair the moving average and linear models; (b) the simultaneous autoregressive and autoregressive response model pair with a Bessel function (modified of the second kind and order one) rather than the Gaussian semi-variogram model; (c) both specification error and measurement error can give rise to the nugget effect discussed in geostatistics; (d) restricting estimation to a geographic subregion introduces edge effects that increasingly bias semi-variogram model parameter estimates as the degree of spatial autocorrelation increases toward its upper limit; and (e) the theoretical spectral density function for a simultaneous autoregressive model is a direct extension of that for the conditional autoregressive model.