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.     

美国夏威夷州标准化基础教育改革:理念、路径与启示

在美国标准化教育改革思潮和夏威夷独特教育价值观的影响下,夏威夷州开始进行大刀阔斧的标准化基础教育改革.此次改革极具鲜明特色,在规划政策推行、领导团队搭建和配套制度建设三方面的系列措施取得了阶段性成功,但同时也面临着资本过度干预教育的困境.美国夏威夷州的标准化基础教育改革为我国提供了镜鉴.我国基础教育改革需要制定统筹兼顾的教育规划,发掘本土文化的教育价值;集结教育系统的内外力量,设计分工合理的运行框架;设定并行不悖的衡量标准,放宽教育目标的达成方式;发挥宏观调控的积极作用,弥补教育管理的薄弱环节.     

新常态下货币供给对工业经济的非对称冲击——兼论冲击路径的情景设计与分析

货币政策冲击对工业产出和价格的非对称影响，是新常态下把握好货币供给政策的方向、力度和节奏的重要参考依据，有助于提升货币供给政策的针对性、灵活性和前瞻性。局部投影方法在不同区制下，计算工业产出和价格对货币供给冲击的脉冲响应结果表明：货币供给冲击对工业产出的影响具有不确定性，且总体上表现为中性特征；而货币供给冲击对工业价格的影响不仅在不同区制下，而且在新常态前后均表现出显著的差异性和非对称性，总体来说是短期有效，长期中性的。情景设计的分析结果显示新常态下采用增加货币供给的政策来刺激工业经济是不可取的，其作用效果可能出现工业产出停滞不前，工业价格急剧飙升的工业滞胀。因此，需要从工业产业升级，工业技术创新等工业供给侧寻求工业经济新的增长点和动力机制。     

孔隙介质中滞留聚合物分子的粘弹效应系数

本文在文献[1]的基础上做了进一步的试验研究,发现慢速降压过程流速对时间的依赖关系呈指数曲线形式,同时进行了慢速升压试验,同样发现流速与时间的指数关系。文中对文献[1]定义的附加残余效应系数提出了修改,重新定义为滞留分子粘弹效应系数,对降压过程和升压过程的粘弹效应系数进行了对比。通过岩心出口液浓度数据,证实了文中描述的粘弹效应机理和分子构象改变的物理模型的可靠性。     

A new generalized Weibull distribution in income economic inequality curves

Researchers have been developing various extensions and modified forms of the Weibull distribution to enhance its capability for modeling and fitting different data sets. In this note, we investigate the potential usefulness of the new modification to the standard Weibull distribution called odd Weibull distribution in income economic inequality studies. Some mathematical and statistical properties of this model are proposed. We obtain explicit expressions for the first incomplete moment, quantile function, Lorenz and Zenga curves and related inequality indices. In addition to the well-known stochastic order based on Lorenz curve, the stochastic order based on Zenga curve is considered. Since the new generalized Weibull distribution seems to be suitable to model wealth, financial, actuarial and especially income distributions, these findings are fundamental in the understanding of how parameter values are related to inequality. Also, the estimation of parameters by maximum likelihood and moment methods is discussed. Finally, this distribution has been fitted to United States and Austrian income data sets and has been found to fit remarkably well in compare with the other widely used income models.     

The context of employment discrimination: interpreting the findings of a field experiment

Although field experiments have documented the contemporary relevance of discrimination in employment, theories developed to explain the dynamics of differential treatment cannot account for differences across organizational and institutional contexts. In this article, I address this shortcoming by presenting the main empirical findings from a multi‐method research project, in which a field experiment of ethnic discrimination in the Norwegian labour market was complemented with forty‐two in‐depth interviews with employers who were observed in the first stage of the study. While the experimental data support earlier findings in documenting that ethnic discrimination indeed takes place, the qualitative material suggests that theorizing in the field experiment literature have been too concerned with individual and intra‐psychic explanations. Discriminatory outcomes in employment processes seems to be more dependent on contextual factors such as the number of applications received, whether requirements are specified, and the degree to which recruitment procedures are formalized. I argue that different contexts of employment provide different opportunity structures for discrimination, a finding with important theoretical and methodological implications.     

The identification of logistic regression models with errors in the variables

The simple logistic regression model with normal measurement error and normal regressor is shown to be identifiable without any extra information about the measurement error. The multiple logistic regression model with more than one regressor variable measured with error is not identifiable. If the covariance matrix of the measurement error is known up to a scalar factor, the model is identified. Further we discuss why in spite of the identifiability the models cannot be estimated in a reasonable way without extra information about the measurement error.