Improved Transferability of Data‐Driven Damage Models Through Sample Selection Bias Correction

Damage models for natural hazards are used for decision making on reducing and transferring risk. The damage estimates from these models depend on many variables and their complex sometimes nonlinear relationships with the damage. In recent years, data‐driven modeling techniques have been used to capture those relationships. The available data to build such models are often limited. Therefore, in practice it is usually necessary to transfer models to a different context. In this article, we show that this implies the samples used to build the model are often not fully representative for the situation where they need to be applied on, which leads to a “sample selection bias.” In this article, we enhance data‐driven damage models by applying methods, not previously applied to damage modeling, to correct for this bias before the machine learning (ML) models are trained. We demonstrate this with case studies on flooding in Europe, and typhoon wind damage in the Philippines. Two sample selection bias correction methods from the ML literature are applied and one of these methods is also adjusted to our problem. These three methods are combined with stochastic generation of synthetic damage data. We demonstrate that for both case studies, the sample selection bias correction techniques reduce model errors, especially for the mean bias error this reduction can be larger than 30%. The novel combination with stochastic data generation seems to enhance these techniques. This shows that sample selection bias correction methods are beneficial for damage model transfer.     

城市空间的改造、生产到正义侵蚀（巴黎1850—1890）

1850—1890年以奥斯曼为代表的统治者对巴黎城市空间进行功能性改造，塑造了巴黎新的景观社会并完成了空间生产化、秩序化、政治化的重构。资产阶级借助地租杠杆，利用空间政治工具性和政治功能性进行资本扩张的同时，也实现了阶层分化和新身份政治的形成。资本投机下的空间改造与生产使得巴黎无产阶级生存与发展的权益逐步被蚕食、侵害和剥夺，无产者对资产阶级的空间改造逐渐产生了由认同—消解—反抗的转向，空间正义意识开始觉醒。通过对城市空间规划改造中的阶级立场分析，论证空间正义与城市发展、阶层融合、社会排斥之间的联系机理，阐明资本主义空间规划与空间生产的固有缺陷，对当代城市的空间规划、贫困问题、社会排斥、城市包容性发展、环境更新与治理等现实问题提供新的视角启发与理路审视。     

论"通知—删除"规则的性质——以平台自治为视角

"通知—删除"规则的法律条文并没有赋予平台自治的空间,但是平台自治的需求已经"凸显".免责条款理论表面上能保障平台自治,但是并不符合我国的实际.归责条款理论是我国的通说,其扼杀了平台自治的空间,司法实践对此虽有调和,但是难以济事.我国的"通知—删除"规则系特定的历史背景下的产物,其在性质上仅仅是行为标准.在侵权行为的认定上,违反"通知—删除"规则的情形并非侵权的充分条件.事实上,这一行为标准的违反在侵权法上的意义仅仅作为主观过错的证据,电商平台可以反证其不具有过错.司法实践中亦有区别对待"通知—删除"规则的违反和侵权之认定的做法.明晰此点方可保障平台自治,同时亦实现电商平台对用户监管之目的.     

科技创新、产业复杂度与经济增长

科技创新能够通过产业复杂度的变化对经济增长产生影响.以1995—2019年世界银行和哈佛大学Atlas数据库的科技创新为研究样本,运用中介效应检验方法,考察科技创新如何通过纺织类、农业类、钻石类、矿产类、金属类、化工类、汽车类、设备类和电子类的产业复杂度变化来影响国民生产总值,从而揭示了科技创新如何通过产业复杂度的变化影响经济增长的机理.研究结果表明:从总体上看,科技创新影响经济增长的过程中,产业复杂度的中介效应量为90.83％,具有显著性,其中农业类、钻石类以及矿产类相关系数为负,其他类别相关系数为正,电子类作用程度最高.区分经济体类型的研究结果显示:产业复杂度的中介效应存在异质性,发达经济体、亚洲经济体、技术密集型经济体存在相对优势,而且科技创新促进经济增长开启了"机会窗口期",后发经济体可以实现"弯道超车".这一研究结论有助于丰富科技创新领域的相关成果,能够为引导产业转型升级方向、提高国家经济增长能力提供理论依据和经验借鉴.     

Multiple event times in the presence of informative censoring: modeling and analysis by copulas

Motivated by a breast cancer research program, this paper is concerned with the joint survivor function of multiple event times when their observations are subject to informative censoring caused by a terminating event. We formulate the correlation of the multiple event times together with the time to the terminating event by an Archimedean copula to account for the informative censoring. Adapting the widely used two-stage procedure under a copula model, we propose an easy-to-implement pseudo-likelihood based procedure for estimating the model parameters. The approach yields a new estimator for the marginal distribution of a single event time with semicompeting-risks data. We conduct both asymptotics and simulation studies to examine the proposed approach in consistency, efficiency, and robustness. Data from the breast cancer program are employed to illustrate this research.

     

Has Opposition to Immigration Increased in the United States after the Economic Crisis? An Experimental Approach

We employ two population‐level experiments to accurately measure opposition to immigration before and after the economic crisis of 2008. Our design explicitly addresses social desirability bias, which is the tendency to give responses that are seen favorably by others and can lead to substantial underreporting of opposition to immigration. We find that overt opposition to immigration, expressed as support for a closed border, increases slightly after the crisis. However, once we account for social desirability bias, no significant increase remains. We conclude that the observed increase in anti‐immigration sentiment in the post‐crisis United States is attributable to greater expression of opposition rather than any underlying change in attitudes.     

Inferences on the Means of Two Log-Normal Distributions: A Computational Approach Test

In this article, we propose a novel approach for testing the equality of two log-normal populations using a computational approach test (CAT) that does not require explicit knowledge of the sampling distribution of the test statistic. Simulation studies demonstrate that the proposed approach can perform hypothesis testing with satisfying actual size even at small sample sizes. Overall, it is superior to other existing methods. Also, a CAT is proposed for testing about reliability of two log-normal populations when the means are the same. Simulations show that the actual size of this new approach is close to nominal level and better than the score test. At the end, the proposed methods are illustrated using two examples.     

A new long-term survival model with dispersion induced by discrete frailty

Lifetime Data Analysis - Frailty models are generally used to model heterogeneity between the individuals. The distribution of the frailty variable is often assumed to be continuous. However, there...     

Efficient Estimation in Heteroscedastic Partially Linear Varying Coefficient Models

This article considers statistical inference for the heteroscedastic partially linear varying coefficient models. We construct an efficient estimator for the parametric component by applying the weighted profile least-squares approach, and show that it is semiparametrically efficient in the sense that the inverse of the asymptotic variance of the estimator reaches the semiparametric efficiency bound. Simulation studies are conducted to illustrate the performance of the proposed method.