Hierarchical Bayesian Modeling of Post-Earthquake Ignition Probabilities Considering Inter-Earthquake Heterogeneity

Post-earthquake fires are high-consequence events with extensive damage potential. They are also low-frequency events, so their nature remains underinvestigated. One difficulty in modeling post-earthquake ignition probabilities is reducing the model uncertainty attributed to the scarce source data. The data scarcity problem has been resolved by pooling the data indiscriminately collected from multiple earthquakes. However, this approach neglects the inter-earthquake heterogeneity in the regional and seasonal characteristics, which is indispensable for risk assessment of future post-earthquake fires. Thus, the present study analyzes the post-earthquake ignition probabilities of five major earthquakes in Japan from 1995 to 2016 (1995 Kobe, 2003 Tokachi-oki, 2004 Niigata–Chuetsu, 2011 Tohoku, and 2016 Kumamoto earthquakes) by a hierarchical Bayesian approach. As the ignition causes of earthquakes share a certain commonality, common prior distributions were assigned to the parameters, and samples were drawn from the target posterior distribution of the parameters by a Markov chain Monte Carlo simulation. The results of the hierarchical model were comparatively analyzed with those of pooled and independent models. Although the pooled and hierarchical models were both robust in comparison with the independent model, the pooled model underestimated the ignition probabilities of earthquakes with few data samples. Among the tested models, the hierarchical model was least affected by the source-to-source variability in the data. The heterogeneity of post-earthquake ignitions with different regional and seasonal characteristics has long been desired in the modeling of post-earthquake ignition probabilities but has not been properly considered in the existing approaches. The presented hierarchical Bayesian approach provides a systematic and rational framework to effectively cope with this problem, which consequently enhances the statistical reliability and stability of estimating post-earthquake ignition probabilities.     

政府减排目标、产业结构与污染减排

政府是污染减排的重要主体,了解其行为对污染减排的作用对提升污染减排效果及实现中国绿色发展具有重要意义。创造性地将政府减排目标纳入研究框架,构建面板门槛模型,从工业污染排放总量的角度分析政府减排目标、产业结构、经济规模等因素对地方污染减排的影响,并用工业污染物强度进行稳健性检验。结果显示,政府减排目标对污染减排的作用存在阶段性不同:经济发展初级阶段,政府减排目标对污染排放总量的作用方向为正; 经济发展水平较高时,作用方向为负; 两者之间存在适应性调整阶段,作用方向具有不确定性,但总体由正向作用向负向作用转变。产业结构对工业污染排放总量的作用方向因污染物种类而异,经济规模对工业污染排放总量作用方向为正。     

A New Methodology for Before–After Safety Assessment Using Survival Analysis and Longitudinal Data

The widely used empirical Bayes (EB) and full Bayes (FB) methods for before–after safety assessment are sometimes limited because of the extensive data needs from additional reference sites. To address this issue, this study proposes a novel before–after safety evaluation methodology based on survival analysis and longitudinal data as an alternative to the EB/FB method. A Bayesian survival analysis (SARE) model with a random effect term to address the unobserved heterogeneity across sites is developed. The proposed survival analysis method is validated through a simulation study before its application. Subsequently, the SARE model is developed in a case study to evaluate the safety effectiveness of a recent red‐light‐running photo enforcement program in New Jersey. As demonstrated in the simulation and the case study, the survival analysis can provide valid estimates using only data from treated sites, and thus its results will not be affected by the selection of defective or insufficient reference sites. In addition, the proposed approach can take into account the censored data generated due to the transition from the before period to the after period, which has not been previously explored in the literature. Using individual crashes as units of analysis, survival analysis can incorporate longitudinal covariates such as the traffic volume and weather variation, and thus can explicitly account for the potential temporal heterogeneity.     

Uniform consistency rate of kNN regression estimation for functional time series data

In this paper, we investigate the k-nearest neighbours (kNN) estimation of nonparametric regression model for strong mixing functional time series data. More precisely, we establish the uniform almost complete convergence rate of the kNN estimator under some mild conditions. Furthermore, a simulation study and an empirical application to the real data analysis of sea surface temperature (SST) are carried out to illustrate the finite sample performances and the usefulness of the kNN approach.     

中国当代人口发展分析

以人为本的科学发展观必然要求我们在一切发展序列中首先关注人口发展,中国人口发展在中国社会发展框架中具有绝对优先的工具价值和目的意义.中国作为发展中国家与作为人口最多的国家两者之间在很大程度上具有互为因果的内在关系,充分认识中国人口发展现状具有多元化的重要意义.中国人口发展状况主要表现为人口数量多、人口质量低和人口结构不合理.中国人口现代化是中国其它现代化的强力引擎,中国人口发展的基本创新路径是城市化发展路径、市场化发展路径、民主化发展路径.     

试论投资基金的治理结构

投资基金的治理结构包含三个层次,即基金的各方当事人权利义务的制度安排、基金内部约束机制、外部市场压力及监管制度。针对我国基金治理结构目前存在的问题,可通过引入独立董事制度、将基金经理的报酬机制与公司的经营业绩挂钩、增强外部市场的竞争压力等途径,使之逐步完善。     

湖北省乡镇企业1978—2002年发展概况、问题及对策研究

1978～2002年,湖北省乡镇企业在企业单位数量、对经济增长贡献及转移农村剩余劳动力等方面对该省经济产生了重要的推动作用。然而,随着市场经济体制的深入发展和不断完善,乡镇企业发展也遇到了前所未有的困难。本文在深入分析当前乡镇企业所面临的问题基础上,提出了乡镇企业未来发展的战略对策。     

中日文动宾结构初探

文章通过中文的动宾结构与相应的日语谓语形式进行比较,阐明中日动宾结构的异同,进而分析中日自他动词的差异,指出学习日语动词时易犯的毛病及其对策。     

Juvenile Delinquency Under Conditions of Rapid Social Change

Increased juvenile delinquency can be seen as an indicator for a deteriorating social fabric under conditions of rapid social change. Criminological theories suggest, however, that such conditions do not per se produce delinquency: They force youth into prodelinquent leisure activities with peers, leading to an endorsement of delinquent behavior and offering the infrastructure for it. Resources acquired in family and public life, however, may prevent youth from drifting into such prodelinquent leisure activities and indirectly from delinquent behavior. Empirical tests of these hypotheses have to employ simultaneous analyses of societal-level and individual-level data. On the basis of an international youth study, the paper undertakes such an analysis: In the years 1992–95, data from 42 independent samples of seventh graders from East and West Germany, Poland, Russia, Bulgaria, Slovakia, Hungary, Czechia, and Greece were surveyed. Data on deviant school behavior, delinquent drift, nurturant parenting, and subjective feelings of justice in public were obtained from 7282 thirteen- to fourteen-year-olds. Processes of rapid social change were incorporated as data on changes in GNP in the years proceeding the surveys. Analyses show that delinquent drift is a valid predictor of deviant school behavior only on the individual level. The extent to which adolescents engage in prodelinquent peer activities depends more on the cultural context in which adolescents live than on their personal experience in the family and in public. Nurturant parenting does, however, covary negatively with deviant school behavior irrespective of level of analysis.     

论数学教育中的数学观念体系

本文从培养数学观念的角度，就数学教育如何培养人们的科学思维方式和形成良好的思维习惯作一论述。