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.     

Toward a sociology of global comparative placemaking

I call for a globally informed sociology of comparative placemaking that integrates historical and contemporary processes and includes the ephemeral, institutional, and personal. By placemaking, I am referring to the explicit or tacit cooperation among people to create, maintain, and give meaning to places in space through bodily occupation given differential resources and constraints. I review select place, space, and community-based literature about urban, Black, migrant, LGBTQ, and international populations to think about how we can build upon and integrate multiple theoretical, methodological, and epistemological insights to form an explicit placemaking research agenda. A US focus on neighborhoods contrasts with a comparative examination of global urban networks, social polarization, and transformation of the built environment in the interdisciplinary field of global urban studies (Ren, 2018). I argue for a placemaking research agenda that bridges insight from US Urban Sociology with Global Urban Studies to consider how various structures and actors constrain and facilitate place projects. With a globally reaching and comparatively informed sociology of placemaking, we can illuminate our multi-structured story of place and agency in context. We can answer questions about how and why we co-create and are simultaneously disciplined by the process of creation.     

The value of being precise

This study investigates how individuals assess imprecise information. We focus on two essential dimensions of decision under uncertainty, outcomes and probabilities, and their respective precision. We believe the precision of information is highly relevant in the investment setting, as reflected in the well-known “home (familiarity) bias”, and the outcome and probability dimensions, separately or jointly, may affect investors’ knowledge of uncertainty and perceived risk of the investment options, and subsequently affect investors’ choices. To test this conjecture, we conducted three experiments. Our results show that 1) participants demonstrate a pattern of preference for precision and aversion of extreme vagueness and associate vagueness with higher perceived risk and lower investment (experiments one and two); 2) participants prefer vague outcome information to vague probability information (experiment two); 3) familiarity indeed positively affects the precision of estimated values, but this association is stronger for the outcome dimension than for probabilities (experiment three). Our results confirm that precision in information, especially in the outcome dimension has an impact on investors’ resource allocation choices.     

Price bias and common practice in option pricing

Generally, the semiclosed-form option pricing formula for complex financial models depends on unobservable factors such as stochastic volatility and jump intensity. A popular practice is to use an estimate of these latent factors to compute the option price. However, in many situations this plug-and-play approximation does not yield the appropriate price. This article examines this bias and quantifies its impacts. We decompose the bias into terms that are related to the bias on the unobservable factors and to the precision of their point estimators. The approximated price is found to be highly biased when only the history of the stock price is used to recover the latent states. This bias is corrected when option prices are added to the sample used to recover the states' best estimate. We also show numerically that such a bias is propagated on calibrated parameters, leading to erroneous values. The Canadian Journal of Statistics 48: 8–35; 2020 © 2019 Statistical Society of Canada     

城市综合体建设面临的一系列问题探讨--以南通市为例

随着房地产调控和城市化进程的加快，商业地产越来越受到开发商的青睐。城市综合体作为商业地产的典型代表以其多结构多层级的功能组合迅速提升区域价值而拥有了“城中之城”的美誉，在东部地区二三线城市大量涌现。但城市综合体带动城市发展的同时，也引发了一系列风险亟待关注。     

Visualization of generalized mean estimators using auxiliary information in survey sampling

Abstract

The mean estimators with ratio depend on multiple auxiliary variables and unknown parameters in a finite population setting. We propose a new generalized approach with matrices for modeling the mutivariate mean estimators with two auxiliary variables. Our approach brings naturally a graphical analysis for comparing mean estimators.     

市场分割、政企关系与异地市场拓展

中国的市场仍旧存在某种程度的分割，如何突破这种市场分割到异地拓展市场是企业要考虑的现实问题。以前的研究主要是从省级层面或国家层面进行宏观分析。文章创新地从政企关系视角入手来考察市场分割情形下微观层面的企业异地市场拓展，也是首先把市场分割（和异地市场）分为省内（本市外）市场、省外市场和海外市场三个不同层面来研究的论文。用世界银行的调查数据从微观企业个体层面检验了企业异地市场拓展的可能。实证研究结果发现，市场分割确实阻碍了企业异地市场拓展，但这仅限于省内市场而不是省外市场。此外，市场分割是有方向性的，从地方保护主义严重的市场里走出来的企业更容易拓展异地市场，但此结论仅适用于国内市场拓展而不适用于海外市场拓展。良好的政企关系是有利于企业异地市场拓展的，但仅限于省外市场，对省内市场以及海外市场是无效的。文章解释了其中的原因，并分析了对于企业实践的启示。     

试论延吉城市旅游形象设计

在延吉城市旅游形象的诸要素中,民俗要素最为重要,因此,在对延吉城市旅游形象进行定位时,无论是从延吉城市形象的硬件上(如交通、餐饮),还是在城市旅游形象的软件上(如市民素质、民俗民风等方面),都要突出民俗特色,同时要用多种形式大力宣传。     

虚拟空间交织的取向原则

虚拟空间交织是人们常用的思维与认知方式之一。本文通过对交织及其原则的介绍,描述了虚拟空间交织的运作,指出虚拟空间交织构建中主观取向的原则应为最佳关联。