建筑节能激励政策的非对称博弈分析

本文探讨了建筑节能领域中政府与房地产商群体之间的非对称博弈问题,分析了该博弈所具有的模仿者动态模型、斯坦克尔伯格模型的特点,并构造了两者关于建筑节能激励政策的非对称博弈模型,最后对双方分别提出了博弈策略建议。     

客运专线运营对区域经济的影响

铁路客运专线的运营将提高干线的客货运输能力,降低社会运输总成本,带动高新产业发展,节约旅行时间,带动第三产业的发展等.本文建立了数学模型,以秦沈客运专线为例进行了定量分析,为客运专线的规划提供参考依据.     

Asymptotic bias in the linear mixed effects model under non-ignorable missing data mechanisms

Summary.  In longitudinal studies, missingness of data is often an unavoidable problem. Estimators from the linear mixed effects model assume that missing data are missing at random. However, estimators are biased when this assumption is not met. In the paper, theoretical results for the asymptotic bias are established under non-ignorable drop-out, drop-in and other missing data patterns. The asymptotic bias is large when the drop-out subjects have only one or no observation, especially for slope-related parameters of the linear mixed effects model. In the drop-in case, intercept-related parameter estimators show substantial asymptotic bias when subjects enter late in the study. Eight other missing data patterns are considered and these produce asymptotic biases of a variety of magnitudes.     

On pooling data summaries in the absence of interactions “response-by-study”

The standard hypothesis testing procedure in meta-analysis (or multi-center clinical trials) in the absence of treatment-by-center interaction relies on approximating the null distribution of the standard test statistic by a standard normal distribution. For relatively small sample sizes, the standard procedure has been shown by various authors to have poor control of the type I error probability, leading to too many liberal decisions. In this article, two test procedures are proposed, which rely on thet—distribution as the reference distribution. A simulation study indicates that the proposed procedures attain significance levels closer to the nominal level compared with the standard procedure.     

On Block Updating in Markov Random Field Models for Disease Mapping

Gaussian Markov random field (GMRF) models are commonly used to model spatial correlation in disease mapping applications. For Bayesian inference by MCMC, so far mainly single-site updating algorithms have been considered. However, convergence and mixing properties of such algorithms can be extremely poor due to strong dependencies of parameters in the posterior distribution. In this paper, we propose various block sampling algorithms in order to improve the MCMC performance. The methodology is rather general, allows for non-standard full conditionals, and can be applied in a modular fashion in a large number of different scenarios. For illustration we consider three different applications: two formulations for spatial modelling of a single disease (with and without additional unstructured parameters respectively), and one formulation for the joint analysis of two diseases. The results indicate that the largest benefits are obtained if parameters and the corresponding hyperparameter are updated jointly in one large block. Implementation of such block algorithms is relatively easy using methods for fast sampling of Gaussian Markov random fields ( Rue, 2001 ). By comparison, Monte Carlo estimates based on single-site updating can be rather misleading, even for very long runs. Our results may have wider relevance for efficient MCMC simulation in hierarchical models with Markov random field components.     

Conditions for Non-confounding and Collapsibility without Knowledge of Completely Constructed Causal Diagrams

In this paper, we discuss several concepts in causal inference in terms of causal diagrams proposed by Pearl (1993 , 1995a , b ), and we give conditions for non-confounding, homogeneity and collapsibility for causal effects without knowledge of a completely constructed causal diagram. We first introduce the concepts of non-confounding, conditional non-confounding, uniform non-confounding, homogeneity, collapsibility and strong collapsibility for causal effects, then we present necessary and sufficient conditions for uniform non-confounding, homegeneity and collapsibilities, and finally we show sufficient conditions for non-confounding, conditional non-confounding and uniform non-confounding.     

区域发展潜力的评价方法及其应用

阐述了区域可持续发展的涵义 ,并从系统的角度对区域可持续发展进行了分析 ,提出了区域发展潜力的概念。构建了区域发展潜力的评价模型。最后对H市的发展潜力进行了评价     

动物遗传育种系列课程双螺旋循环教学模式的建立与实践

根据动物遗传育种系列课程的结构、教学特点、本学科学生的层次性、学科发展和对教师多能性的要求 ,对该系列课程进行了教学内容、教学方式、教学手段的全面改革 ,构建了一套双螺旋循环教学模式 ,即教师与课程的螺旋循环链和学生层次与学习过程的螺旋循环链。这两条“教”、“学”互动的螺旋循环链有机结合 ,每完成一次循环教学过程 ,双螺旋上升一个螺距 ,教师的教学水平提高 ,学生的综合素质和学历提高一个层次。     

多元化计量模式的现实思考--历史成本与公允价值择优并存

多元化计量模式的现实思考——历史成本与公允价值择优并存@谢桂芬$宁波高等专科学校经管系!浙江宁波315010~~     

血管的三维重建

构建了血管的三维重建模型 ,并给出了模型的算法及其求解结果 .