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.     

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.

     

理智与情感:为历史“正名”的方法——从刘保昌长篇小说《楚武王》谈起

历史书写中的“最炫流行风”在今天的文化市场上大行其道——用拆解、谐谑、碎片化、戏拟等方式拉平历史的深度,以“傲慢与偏见”来充抵叙述历史的自信,也经由这种时尚化的叙述使历史以“轻松一刻”的形式实现消费欲望的满足.刘保昌的《楚武王》则疏离“流行前线”,以史料为据,正本清源,守正而出新,为历史“正名”,以彰显历史意识、历史理性的写作姿态,以坚持文学之理想力量的叙事激情,以有文化承担的叙事态度显示出对当代历史小说叙事品格与尊严的坚守.     

A modified common factor model for modelling mortality jointly for both sexes

Journal of Population Research - There is an increasing attention on the joint modelling of multiple populations. Populations are related in several ways, such as neighbouring countries, females...     

1950年代:“本质—特征论”文学定义的形成及影响

1950年代形成了"本质—特征论"的文学定义,即先界定文学的意识形态本质,再界定文学是用形象的方式来反映社会生活、体现意识形态的特征。这一定义的思维方式是先界定事物的普遍性,再界定事物的特殊性,突出事物的普遍性关联,轻视事物的独特性质的揭示,使得文学研究本应着重研究文学的特殊性成为空话,不利于认识文学自身的规律。1980年代的文学审美论试图突破这种定义方式,但1990年代以来,反本质主义的文学语境论再次回到从事物的关联性定义事物的思维老路,文学自身本质问题受到质疑,弱化了文学与审美关联的重要性与必要性。     

Partial Identification of Economic Mobility: With an Application to the United States

Abstract

The economic mobility of individuals and households is of fundamental interest. While many measures of economic mobility exist, reliance on transition matrices remains pervasive due to simplicity and ease of interpretation. However, estimation of transition matrices is complicated by the well-acknowledged problem of measurement error in self-reported and even administrative data. Existing methods of addressing measurement error are complex, rely on numerous strong assumptions, and often require data from more than two periods. In this article, we investigate what can be learned about economic mobility as measured via transition matrices while formally accounting for measurement error in a reasonably transparent manner. To do so, we develop a nonparametric partial identification approach to bound transition probabilities under various assumptions on the measurement error and mobility processes. This approach is applied to panel data from the United States to explore short-run mobility before and after the Great Recession.     

高含水期油藏层间压力结构差异量化方法研究

由于长期注水开发和层间非均质性影响，高含水期油藏各小层层间压力结构差异严重，掌握差异状况是合理调整的重要依据。针对现场分层测压资料少，单层压力资料获取困难的情况，应用渗流力学原理建立了高含水期地层层间压力结构差异量化数学模型，模型的关键参数可以通过生产数据计算获得。枣园油田的实例验证表明，高含水油藏层间压力存在明显差异，该方法能够确定各小层的压力差异状况。量化计算结果和实测资料相接近，有利于认清开发矛盾，为合理调整提供技术依据。     

Towards Uniformly Efficient Trend Estimation Under Weak/Strong Correlation and Non‐stationary Volatility

In this paper, we consider the deterministic trend model where the error process is allowed to be weakly or strongly correlated and subject to non‐stationary volatility. Extant estimators of the trend coefficient are analysed. We find that under heteroskedasticity, the Cochrane–Orcutt‐type estimator (with some initial condition) could be less efficient than Ordinary Least Squares (OLS) when the process is highly persistent, whereas it is asymptotically equivalent to OLS when the process is less persistent. An efficient non‐parametrically weighted Cochrane–Orcutt‐type estimator is then proposed. The efficiency is uniform over weak or strong serial correlation and non‐stationary volatility of unknown form. The feasible estimator relies on non‐parametric estimation of the volatility function, and the asymptotic theory is provided. We use the data‐dependent smoothing bandwidth that can automatically adjust for the strength of non‐stationarity in volatilities. The implementation does not require pretesting persistence of the process or specification of non‐stationary volatility. Finite‐sample evaluation via simulations and an empirical application demonstrates the good performance of proposed estimators.     

川东北地区须家河组二段储层差异性分析

随着勘探程度的深入，为了扩大四川盆地天然气勘探领域、寻找新的勘探接替区，四川盆地的勘探区域由盆内逐渐向盆缘延伸。在这种背景下，川东北地区须家河组二段相继取得新的勘探成果，但在勘探开发过程中逐渐暴露了诸如区块之间气井产能差异大，储层的碎屑组分、结构及厚度、物性、孔隙结构差异明显等问题，制约了勘探开发的步伐。针对上述问题，根据岩芯观察描述、分析化验资料及测井解释成果，从沉积、成岩方面入手，对比剖析了川东北龙岗和营山地区须二段储层特征的差异性及其成因，认为远离物源区和高能水体的反复淘洗是造成储层差异性的首要因素，强烈的压实作用和多期石英加大对储层差异性起关键作用，自生绿泥石衬边胶结和长石选择性溶蚀最终决定了储层差异性。从而解释了气藏勘探开发中遇到的诸多问题，对有效指导该区的下一步勘探开发工作具有重要意义。     

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.