TESTING THE SPATIAL SCALE AND THE DYNAMIC STRUCTURE IN REGIONAL MODELS (A CONTRIBUTION TO SPATIAL ECONOMETRIC SPECIFICATION ANALYSIS)*

This article addresses the problem of specification uncertainty in modeling spatial economic theories in stochastic form. It is ascertained that the traditional approach to spatial econometric modeling does not adequately deal with the type and extent of specification uncertainty commonly encountered in spatial economic analyses. Two alternative spatial econometric modeling procedures proposed in the literature are reviewed and shown to be suitable for analyzing systematically two sources of specification uncertainty, viz., the level of aggregation and the spatio-temporal dynamic structure in multiregional econometric models. The usefulness of one of these specification procedures is illustrated by the construction of a simple multiregional model for The Netherlands.     

Modelling life-science clusters in terms of resources and capabilities

Life-science clusters have been extensively researched; however, comprehensive models in terms of resources and capabilities appear to be rare. Such models are needed to assist the analysis of sources of success of some clusters, to distinguish successful from less successful or mature from early stage locations, and to help formulate templates for developing emerging and peripheral locations. Due to the scarcity of systemic and holistic models, a model is proposed and is empirically tested during a decade-long research programme combining separate qualitative and quantitative studies analysing four clusters: Central Scotland, Oxford, South West England and Ireland. Through successive stages of testing, the model is shown to be a reliable tool capable of assessing cluster traits and performance in terms of resources and capabilities, by uncovering systematic differences across the studied locations. The model application generates surprising findings which could not have been reached through simpler measures and which would be difficult to identify or theorize without the model. Confirmed are consistent associations across cluster resources and capabilities, outcomes, and institutional conditions. The model helps distinguish globally leading, mature clusters from peripheral, less-mature locations and assists the theorization of locations across life-cycle stages.     

Model Uncertainty in Matrix Exponential Spatial Growth Regression Models

This article considers the most important aspects of model uncertainty for spatial regression models, namely, the appropriate spatial weight matrix to be employed and the appropriate explanatory variables. We focus on the spatial Durbin model (SDM) specification in this study that nests most models used in the regional growth literature, and develop a simple Bayesian model‐averaging approach that provides a unified and formal treatment of these aspects of model uncertainty for SDM growth models. The approach expands on previous work by reducing the computational costs through the use of Bayesian information criterion model weights and a matrix exponential specification of the SDM model. The spatial Durbin matrix exponential model has theoretical and computational advantages over the spatial autoregressive specification due to the ease of inversion, differentiation, and integration of the matrix exponential. In particular, the matrix exponential has a simple matrix determinant that vanishes for the case of a spatial weight matrix with a trace of zero. This allows for a larger domain of spatial growth regression models to be analyzed with this approach, including models based on different classes of spatial weight matrices. The working of the approach is illustrated for the case of 32 potential determinants and three classes of spatial weight matrices (contiguity‐based, k‐nearest neighbor, and distance‐based spatial weight matrices), using a data set of income per capita growth for 273 European regions.     

Bayesian Updating of Seismic Demand Models and Fragility Estimates for Reinforced Concrete Bridges with Two-Column Bents

Probabilistic models have been developed in a previous study by the authors to estimate the seismic deformation demands on structural components of reinforced concrete (RC) bridges with two-column bents. However, such models should be updated to reflect the latest laboratory of field data. Using a Bayesian approach, this article updates a currently available probabilistic model for the deformation demands of columns in bridges with two-column RC bents. The updated model incorporates information from newly available experimental data from shake table tests conducted based on a record of the 1994 Northridge Earthquake for a structural system with three bents with two columns per bent. The updated model is more accurate than the previous one in predicting the deformation demand of bridges with two-column RC bents and reduces the statistical uncertainty due to the addition of new data. As an application, fragility estimates for an example bridge are computed using the updated model both at the component (column) and system (bridge) levels.     

Designing Reliable Center Systems: A Vector Assignment Center Location Problem

The p‐center problem is one of the most important models in location theory. Its objective is to place a fixed number of facilities so that the maximum service distance for all customers is as small as possible. This article develops a reliable p‐center problem that can account for system vulnerability and facility failure. A basic assumption is that located centers can fail with a given probability and a customer will fall back to the closest nonfailing center for service. The proposed model seeks to minimize the expected value of the maximum service distance for a service system. In addition, the proposed model is general and can be used to solve other fault‐tolerant center location problems such as the (p, q)‐center problem using appropriate assignment vectors. I present an integer programming formulation of the model and computational experiments, and then conclude with a summary of findings and point out possible future work.     

ART‐P‐MAP Neural Networks Modeling of Land‐Use Change: Accounting for Spatial Heterogeneity and Uncertainty

Spatial land‐use models over large geographic areas and at fine spatial resolutions face the challenges of spatial heterogeneity, model predictability, data quality, and of the ensuing uncertainty. We propose an improved neural network model, ART‐Probability‐Map (ART‐P‐MAP), tailored to address these issues in the context of spatial modeling of land‐use change. First, it adaptively forms its own network structure to account for spatial heterogeneity. Second, it explicitly infers posterior probabilities of land conversion that facilitates the quantification of prediction uncertainty. Extensive calibration under various test settings is conducted on the proposed model to optimize its utility in seeking useful information within a spatially heterogeneous environment. The calibration strategy involves building a bagging ensemble for training and stratified sampling with varying category proportions for experimentation. Through a temporal validation approach, we examine models’ performance within a systematic assessment framework consisting of global metrics and cell‐level uncertainty measurement. Compared with two baselines, ART‐P‐MAP achieves consistently good and stable performance across experiments and exhibits superior capability to handle the spatial heterogeneity and uncertainty involved in the land‐use change problem. Finally, we conclude that, as a general probabilistic regression model, ART‐P‐MAP is applicable to a broad range of land‐use change modeling approaches, which deserves future research.     

The Encoding-Error Model of Pathway Completion without Vision

We present a model that accounts for errors in short-cutting to complete a triangular pathway by individuals deprived of visual input. The model assumes that systematic error arises from components of navigation concerned with encoding an internal representation of the pathway, rather than the computation of a homeward trajectory or motor output per se. Subjects' tendency to compress the range of actually produced turns and distances, in comparison to the range of correct values, is attributed to regression toward the mean of encoded values during encoding of segments and turns, in the face of uncertainty about the actual values. Individual-subject variations are attributed to differences in the encoding-function parameters, not to variations in the processes themselves. The model provides excellent accounts of data obtained with triangular pathways but fares less well when pathway complexity increases, at which point errors do not appear to be solely attributable to encoding processes. The sources of error identified by the model are likely to play a role in navigation more generally.     

Geospatial modeling of pedestrian transportation networks: a case study from precolumbian Oaxaca,Mexico

Using accumulated cost surfaces and various pathfinding techniques within Geographic Information Systems (GIS) software, archaeologists and other spatial scientists have developed increasingly sophisticated models of human movement. Despite their utility, these approaches can be limited because standard GIS software cannot model movement (1) from many origins to many destinations or (2) without specific origins and destinations. Absent these capabilities, it is particularly difficult to model networks of movement over a given tract of land if you are interested in obtaining a more general sense of movement dynamics, not specific site-to-site patterns. In this paper, we present an innovative way of modeling past movement that generates both natural-looking networks and also indicates the degree of traffic that may have existed on any particular segment of those networks. The “From Everywhere to Everywhere” (FETE) model generates networks based on topography and landcover without requiring that origin and destination points be supplied in advance. We apply the FETE model to a case from the southern Mexican state of Oaxaca, a region that has extensive archaeological and ethnohistoric data sets that serve as a test of the efficacy of our technique. A comparison of the FETE output with known late precolumbian and early colonial movement corridors indicates that the method is effective and should be useful for modeling networks in other areas.     

The Neolithic Transition in the Iberian Peninsula: Data Analysis and Modeling

We apply GIS techniques to analyze a carefully selected database of 93 Early Neolithic sites in the Iberian Peninsula. This allows us to study the spatial dynamics of the Neolithic transition in Iberia. We study how the Neolithic was introduced into the peninsula in order to test the hypothesis that the Neolithic was introduced almost simultaneously from two sources: one at the northeast (via the Mediterranean coast) and another one at the south (possibly from Northern Africa). We also analyze how the expansion of the Neolithic transition took place within the Iberian Peninsula and measure local rates of spread in order to identify regions with fast and slow rates (such as the slowdown at the Cantabrian coast). In addition, we attempt to reproduce the main results obtained from the GIS analysis by applying reaction–dispersal models to the expansion of the Neolithic transition in the Iberian Peninsula. We conclude that a model with two sources is a reasonable assumption that agrees better with the archaeological data available at present than a model with a single source.     

UNCERTAINTY AND THE HISTORY OF IDEAS

Intellectual historians often make empirical claims, but can never know for certain if these claims are right. Uncertainty is thus inevitable for intellectual historians. But accepting uncertainty is not enough: we should also act on it, by trying to reduce and report it. We can reduce uncertainty by amassing valid data from different sources to weigh the strengths and weaknesses of competing explanations, rather than trying to “prove” an empirical claim by looking for evidence that fits it. Then we should report our degree of certainty in our claims. When we answer empirical questions in intellectual history, we are not telling our readers what happened: we are telling them how strong we think our evidence is—a crucial shift of emphasis. For intellectual historians, then, uncertainty is subjective, as discussed by Keynes and Collingwood; the paper thus explores three differences between subjective and objective uncertainty. Having outlined the theoretical basis of uncertainty, the paper then offers examples from actual research: Noel Malcolm's work shows how to reduce and report uncertainty about composition, and David Wootton's work shows how to reduce and report uncertainty about beliefs.     

Investigating Global and Local Categorical Map Configuration Comparisons Based on Coincidence Matrices

The simple and intuitive nature of the coincidence matrix has not only made it the current "gold standard" for accuracy assessment (based on a sample of map pixels), but also a common tool for describing difference between two categorical maps (when all pixels are enumerated). It is this latter case of map comparison that this article explores. Coincidence matrices, although providing significant information regarding thematic agreement between two categorical maps (composition), can lack significantly in terms of conveying information about differences or similarities in the spatial arrangement (configuration) of those map categories in geographic space. This article introduces means for distilling the available configuration information from a coincidence matrix while demonstrating some simple categorical map comparisons. Specifically, while the coincidence matrix summarizes per-pixel compositional persistence or change, the introduced technique further quantifies the global and local configurational uncertainty between compared maps. I demonstrate how this quantification of configurational uncertainty can be used to gauge which thematic mismatch types are most significant and how to measure/present local configurational uncertainty in a spatial context. Implementation is through a straightforward mathematical algorithm in R that is illustrated by several examples.     

Handling Large Numbers of Attributes and/or Levels in Conjoint Experiments

Conjoint models have become an established modeling tool for geographical studies. At the core of conjoint models is experimental design, which combines attributes into profiles according to statistical principles. Orthogonal design is the widely used method of experimental design. This method, however, has the problem that task sizes rapidly increase with increasing numbers of attributes and/or levels. Efforts have been spent to overcome this problem, but all existing proposals are based on orthogonal design, providing no radical solution to the problem. In this paper, we attempt to deal with the problem using a new experimental design method that has recently attracted the attention of international statisticians—uniform design, a method that can easily deal with large numbers of attributes and/or levels. The basic idea of this method is to select experimental points (or profiles) that are uniformly scattered in the problem domain, based on the theorem that uniformly distributed experimental points will ensure that the estimated model has the minimum gap with the true model. The key of uniform design is therefore to select designs that have maximum uniformity, which indicates to what extent the experimental points provided by a design are uniformly distributed. The new method is illustrated and tested by a case of intercity transport mode choice.     

Modeling and Control of the CSCEC Multi-Function Testing System

In order to promote the research and development on evaluating the seismic performance of structures, China State Construction Engineering Corporation (CSCEC) planned to construct a large-scale loading testing facility, the Multi-Function Testing System (MFTS). This facility can perform full-scale, real-time, 6-degree-of-freedom static and dynamic testing of rubber bearings and many types of structural components including long columns, shear walls and cross shape joints. The basic performances of the MFTS are a clearance of 9.1 m × 6.6 m × 10 m for specimen installation, maximum x-directional displacement 1500 mm, maximum y-directional velocity 1570 mm/s and maximum z-directional compressive load 108 MN. The system configuration and performance specifications of the MFTS are presented in this paper. The inverse kinematics model and the nonlinear model of the hydraulic servosystem of the MFTS are built. A modified feedback forward kinematics algorithm is developed for real-time control of the MFTS. Internal force characteristics of the loading system are analyzed. The internal force control method based on real-time solution of basis of internal force space is proposed for the system with large motion ranges. The motion controller combining position control loop and internal force control loop is developed. To meet the requirement of simultaneously imposing vertical compressive load and horizontal displacement, a mixed load and displacement controller is designed, where a direct force control loop is used to improve the response speed of the force control and reduce spatial dynamic coupling effects. Finally, a dynamic bearing testing is performed. The test results demonstrate that the system using the proposed controller has good abilities on position tracking, force balance, and load following.     

An Empirically Based Implementation and Evaluation of a Hierarchical Model for Commuting Flows. 一种基于经验的层状通勤流模型实现与评估

This article provides an empirical evaluation of a hierarchical approach to modeling commuting flows. As the gravity family of spatial interaction models represents a benchmark for empirical evaluation, we begin by reviewing basic aspects of these models. The hierarchical modeling framework is the same that Thorsen, Ubøe, and Nævdal (1999) used. However, because some modifications are required to construct a more workable model, we undertake a relatively detailed presentation of the model, rather than merely referring to the presentation in Thorsen, Ubøe, and Nævdal (1999) . The model uses a hierarchical specification of a transportation network and the individual search procedure. Journeys to work are determined by the effects of distance deterrence and of intervening opportunities, and by the location of potential destinations relative to alternatives at subsequent levels in a transportation network. The model calibration uses commuting data from a region in western Norway. The estimated parameter values are reasonable, and the explanatory power is very satisfactory when compared with the results of a competing destinations approach.     

白居塔塔体结构稳定性分析研究

在对白居塔建筑形制调查研究基础上,区分塔体内嵌高山体和内嵌低山体两种情况,确定重力作用以及重力和地震耦合作用两种工况。基于采用岩土摩尔—库伦本构模型的有限元分析技术,对白居塔和山体的耦合结构进行稳定性分析。得出以下结论:自重作用下,整体结构稳定性满足,且有较高的安全稳定系数;白居塔整体结构的刚度较大,整个结构体系属于抗震有利体系;白居寺整体结构基频模态以侧倾为主;在7°(基本加速度0.15 g)多遇地震作用下,两个模型整体结构的抗震稳定性较好,结构不会产生整体性失稳破坏;在8°(基本加速度0.3 g)多遇地震作用下,较高山体模型主体结构基本处于安全状态,较低山体模型主体结构不满足稳定要求;较高山体的模型相对于较低山体的模型,安全稳定性要高。     

Simulating Sources of Uncertainty in Policy Forecasting with a Large-Scale Regional Econometric Model

Long-term forecasts may be helpful in establishing the general framework for a region's policy agenda, and a well-structured economic model offers an opportunity to identify major policy instruments affecting a region's long-term growth. Nevertheless, the uncertainty of long-term forecasts should serve to caution policymakers in interpreting and acting upon such information. To offer perspective on this aspect of forecasts, simulations of the Pittsburgh economy are performed to the year 1995 using a large-scale regional econometric model. The forecasts are based on alternative assumptions concerning the performance of the national economy and the objective conditions characterizing key industries in the region. In this way, the model is used to identify and quantify several major sources of uncertainty in long-term regional forecasts.     

Modelling Uncertainties of Italian Code-Conforming Structures for the Purpose of Seismic Response Analysis

ABSTRACT

This paper describes the multivariate statistical model of the structure-related modelling uncertainty, developed with reference to reinforced concrete, masonry, steel, and seismically isolated buildings, within the framework of the RINTC project. The model describes the variability of material properties as well as the uncertainty associated with the adopted response models. Specific aspects of each structural typology are also discussed, with a focus on the statistical dependence of the random variables in the model. Finally, the paper describes also the efficient sampling procedure adopted. Effect of model uncertainty on response for each typology are discussed in the corresponding papers within this special issue dedicated to the RINTC project.     

城市群体结构及其演进

城市群形成和发展的本质过程和直观表现是城市群体结构或城市群形态结构产生、发展到成熟完善的过程。文章从城市群体结构的概念入手,研究了其基本型式和结构划分的思路,概括了四圈层空间结构模式,即核心首位城市带、城市组群发育带、城市个体分布带、城市群腹地带。分析了其结节性与均质性、网络性、功能性的特征,并对城市群体结构发展动力、阶段及特征加以理论概括。以城市群演化为基点,对城市群体形态结构、类型和演化规律予以阐述,归纳出城市群体结构和城市群形态类型演化的相关模式。     

A Partitioning Model of Urban Retail Structure

A model based on renewal theory generates the number of retail establishments in a place as the outcome of a competitive partitioning process. The available market, measured for example by population or by existing retail sales, is shared among businesses until no market potential market remains. Competing businesses obtain different shares of the market, and the number of establishments is predicted as a discrete random variable. Several alternative formulations are presented of varying generality. One version is successfully tested, using GLIM, on ten business types (SIC two-digit classes) in 232 cities of New York State for 1977 and 1987. The model correctly predicts the form and the variance structure of the relationship between number of establishments and place size. It is shown how the model may be combined with models of city-size distributions to predict aggregate frequency distributions of retail establishments across urban systems.