非线性随机效应模型的异方差性检验

随机效应模型广泛应用于刻画重复测量数据的特征．在该模型中,随机误差的方差包括受试群体内部及受试群体之间两项方差．Ｚｈａｎｇ和 Ｗｅｉｓｓ ２０００年研究了线性随机效应模型的异方差检验,本文对非线性随机效应模型,分别讨论了群体内、群体间和多变量的异方差性的检验问题,得到了检验的ｓｃｏｒｅ统计量,并讨论了三种情形下,相应的ｓｃｏｒｅ函数之间的关系．最后给出一个数值例子说明上述方法的有用性．  

地理权重回归模型在甲状腺肿大中的应用

为解决空间数据存在的空间自相关性或空间异质性,利用地理权重回归模型对四川省2000年碘缺乏病资料进行分析。结果表明地理权重回归模型中的参数估计在各区域并不是完全相等的,而且甲状腺肿大率较高的区域主要位于四川盆地中部及南部的山区和丘陵地带。  

我国居民储蓄函数模型的建立与分析

本文通过建立和分析储蓄函数,对1952年—2001年的我国居民储蓄进行了实证研究,力求在大样本、计量经济建模的完整性两个方面体现出新意,并且探讨了几个易被忽视的问题的实用解决方法。本文研究表明,我国居民的储蓄行为在不同的历史阶段有明显的区别,随着社会经济的发展储蓄行为的无规律性会越来越严重,收入以外的其他影响储蓄的因素主要存在一年和二年的滞后作用。  

捕获再捕获与捕获移出模型的概念、方法和新进展

捕获再捕获与捕获移出研究是数理统计的一个重要方向，它研究如何利用随机样本估计有限群体的总体数目。本文对捕获再捕获与捕获移出模型的历史、基本统计思想、方法及近年来的新进展作一个简要而又较系统的回顾。  

单轴拉伸条件下细观非均匀性岩石损伤局部化和应力应变关系分析

岩石在拉应力状态下的力学特性不同于压应力状态下的力学特性．利用细观力学理论研究了细观非均匀性岩石拉伸应力应变关系包括：线弹性阶段、非线性强化阶段、应力降阶段、应变软化阶段．模型考虑了微裂纹方位角为Weibull分布和微裂纹长度的分布密度函数为Rayleigh函数时对损伤局部化和应力应变关系的影响，分析了产生应力降和应变软化的主要原因是损伤和变形局部化．通过和实验成果对比分析验证了模型的正确性和有效性．  

Meshfree modeling and analysis of physical fields in heterogeneous media

Continuous and discrete variations in material properties lead to substantial difficulties for most mesh-based methods for modeling and analysis of physical fields. The meshfree method described in this paper relies on distance fields to boundaries and to material features in order to represent variations of material properties as well as to satisfy prescribed boundary conditions. The method is theoretically complete in the sense that all distributions of physical properties and all physical fields are represented by generalized Taylor series expansions in terms of powers of distance fields. We explain how such Taylor series can be used to construct solution structures – spaces of functions satisfying the prescribed boundary conditions exactly and containing the necessary degrees of freedom to satisfy additional constraints. Fully implemented numerical examples illustrate the effectiveness of the proposed approach.  

Diffusion dynamics in small-world networks with heterogeneous consumers

Diffusions of new products and technologies through social networks can be formalized as spreading of infectious diseases. However, while epidemiological models describe infection in terms of transmissibility, we propose a diffusion model that explicitly includes consumer decision-making affected by social influences and word-of-mouth processes. In our agent-based model consumers’ probability of adoption depends on the external marketing effort and on the internal influence that each consumer perceives in his/her personal networks. Maintaining a given marketing effort and assuming its effect on the probability of adoption as linear, we can study how social processes affect diffusion dynamics and how the speed of the diffusion depends on the network structure and on consumer heterogeneity. First, we show that the speed of diffusion changes with the degree of randomness in the network. In markets with high social influence and in which consumers have a sufficiently large local network, the speed is low in regular networks, it increases in small-world networks and, contrarily to what epidemic models suggest, it becomes very low again in random networks. Second, we show that heterogeneity helps the diffusion. Ceteris paribus and varying the degree of heterogeneity in the population of agents simulation results show that the more heterogeneous the population, the faster the speed of the diffusion. These results can contribute to the development of marketing strategies for the launch and the dissemination of new products and technologies, especially in turbulent and fashionable markets. This paper won the best student paper award at the North American Association for Computational Social and Organizational Science (NAACSOS) Conference 2005, University of Notre Dame, South Bend, Indiana, USA. Preceding versions of this paper have been presented to the Conference of the North American Association for Computational Social and Organizational Science (NAACSOS), 2005, University of Notre Dame, South Bend, USA and to the Conference of the European Social Simulation Association (ESSA), 2005, Koblenz, Germany. Sebastiano Alessio Delre received his Master Degree in Communication Science at the University of Salerno. After one year collaboration at the Institute of Science and Technologies of Cognition (ISTC, Rome, Italy), now he is a PhD student at the faculty of economics, University of Groningen, the Netherlands. His work focus on how different network structures affect market dynamics. His current application domain concerns Agent-Based Simulation Models for social and economic phenomena like innovation diffusion, fashions and turbulent market. Wander Jager is an associate professor of marketing at the University of Groningen. He studied social psychology and obtained his PhD in the behavioral and social sciences, based on a dissertation about the computer modeling of consumer behaviors in situations of common resource use. His present research is about consumer decision making, innovation diffusion, market dynamics, crowd behavior, stock-market dynamics and opinion dynamics. In his work he combines methods of computer simulation and empirical surveys. He is involved in the management committee of the European Social Simulation Association (ESSA). Marco Janssen is an assistant professor in the School of Human Evolution and Social Change and in the Department of Computer Science and Engineering at Arizona State University. He got his degrees in Operations Research and Applied Mathematics. During the last 15 years, he uses computational tools to study social phenomena, especially human-environmental interactions. His present research focuses on diffusion dynamics, institutional innovation and robustness of social-ecological systems. He combined computational studies with laboratory and field experiments, case study analysis and archeological data. He is an associate editor-in-chief of the journal Ecology and Society.  

压应力状态下细观非均匀性岩石的损伤局部化和应力应变关系分析

利用摩擦弯折裂纹模型研究了受压条件下细观非均匀性岩石的损伤局部化问题和全过程应力应变关系．模型考虑了裂纹相互作用对损伤局部化和全过程应力应变关系的影响，确定了损伤局部化发生的条件，分析了产生损伤局部化的原因．研究表明全过程应力应变关系包括线弹性阶段、非线性强化阶段、应力降和应变软化阶段．通过和实验对比分析验证了模型的正确性和有效性．  

基于离散选择模型DCM的产品差异市场分析

本文从计量经济学的角度,利用离散选择模型对产品差异市场进行了研究,在消费者异质性需求和厂商异质性能力假设下,利用消费者产品性能边际效用递减规律推导出产品性能消费者收益函数,利用产品性能边际成本递增规律推导出产品性能厂商成本关系函数,最后得到消费者需求弹性和厂商在最大创造价值的产品性能决策点.  

Bayesian Analysis of Extreme Values by Mixture Modeling

Modeling of extreme values in the presence of heterogeneity is still a relatively unexplored area. We consider losses pertaining to several related categories. For each category, we view exceedances over a given threshold as generated by a Poisson process whose intensity is regulated by a specific location, shape and scale parameter. Using a Bayesian approach, we develop a hierarchical mixture prior, with an unknown number of components, for each of the above parameters. Computations are performed using Reversible Jump MCMC. Our model accounts for possible grouping effects and takes advantage of the similarity across categories, both for estimation and prediction purposes. Some guidance on the specification of the prior distribution is provided, together with an assessment of inferential robustness. The method is illustrated throughout using a data set on large claims against a well-known insurance company over a 15-year period.