Accounting for Both Random Errors and Systematic Errors in Uncertainty Propagation Analysis of Computer Models Involving Experimental Measurements with Monte Carlo Methods

A Monte Carlo method is presented to study the effect of systematic and random errors on computer models mainly dealing with experimental data. It is a common assumption in this type of models (linear and nonlinear regression, and nonregression computer models) involving experimental measurements that the error sources are mainly random and independent with no constant background errors (systematic errors). However, from comparisons of different experimental data sources evidence is often found of significant bias or calibration errors. The uncertainty analysis approach presented in this work is based on the analysis of cumulative probability distributions for output variables of the models involved taking into account the effect of both types of errors. The probability distributions are obtained by performing Monte Carlo simulation coupled with appropriate definitions for the random and systematic errors. The main objectives are to detect the error source with stochastic dominance on the uncertainty propagation and the combined effect on output variables of the models. The results from the case studies analyzed show that the approach is able to distinguish which error type has a more significant effect on the performance of the model. Also, it was found that systematic or calibration errors, if present, cannot be neglected in uncertainty analysis of models dependent on experimental measurements such as chemical and physical properties. The approach can be used to facilitate decision making in fields related to safety factors selection, modeling, experimental data measurement, and experimental design.     

Direct Inference, Probability, and a Conceptual Gulf in Risk Communication

Differences in the conceptual frameworks of scientists and nonscientists may create barriers to risk communication. This article examines two such conceptual problems. First, the logic of "direct inference" from group statistics to probabilities about specific individuals suggests that individuals might be acting rationally in refusing to apply to themselves the conclusions of regulatory risk assessments. Second, while regulators and risk assessment scientists often use an "objectivist" or "relative frequency" interpretation of probability statements, members of the public are more likely to adopt a "subjectivist" or "degree of confidence" interpretation when estimating their personal risks, and either misunderstand or significantly discount the relevance of risk assessment conclusions. If these analyses of inference and probability are correct, there may be a conceptual gulf at the center of risk communication that cannot be bridged by additional data about the magnitude of group risk. Suggestions are made for empirical studies that might help regulators deal with this conceptual gulf.     

Mixtures of Toxic Agents and Attributable Risk Calculations

Calculations of attributable risks have attracted increasing interest recently. However, these efforts have been limited to mostly one agent, radiation, and no interactions with effects of other toxic agents have been taken into account. This paper outlines a generic approach to the calculation of attributable risks for an exposure to several toxic agents and interaction effects associated with them. In this calculation, the partition of interaction terms between the agents responsible is of particular importance. At present, there are no rules on how to assign equitable shares, so one methodology will be proposed and others discussed briefly. For one example of an assignment, the standard errors of the attributable risks are determined in terms of the uncertainties of the input parameters, thus setting the stage for a comparison of the different shares of responsibility.     

不确定性、学习与新技术序列投资决策

以不同性质不确定性与其解决方式(学习)和效率对投资价值的影响为切入点,研究新技术序列投资行为背后的决策机制与路径.在现有研究基础上,引入企业内部学习的异质性特征,把技术不确定性的解决效率分解为学习能力、累积学习效应与边际学习效应3个层次进行讨论.运用实物期权方法构建包含学习效应的新技术序列投资决策模型,并得到最优决策规则,通过数值方法对不同参数进行比较静态分析,并阐述结果的经济与管理涵义.     

从不确定性看管理研究逻辑及和谐管理理论的启示

在复杂多变的环境下,组织管理面临着因果链无法追踪、整体性割裂和快速应变三大挑战。从组织管理应对不确定性的视角出发,结合对组织管理应对挑战的传统方法的解读,提出和谐管理应对不确定性的思路：以愿景和使命来应对组织目标的不确定性,同时降低因果链无法追踪的影响;以“和则”和“谐则”作为应对不确定性的2种互动机理,在保证效率的同时提高应变能力;以和谐主题和和谐耦合机制来应对组织运行中的不确定性并提升整体性。最后,基于这一思想,提出未来的管理研究应注重愿景和使命的导引作用,和谐主题的合目的性整合作用,以及理性设计的有效实施与诱导演化主动应对互动耦合的支撑作用,特别是日益复杂多变环境下的组织领导人及其团队的作用。     

Operational Slack and Venture Survival

Slack can act as a double‐edged sword. While it can buffer against environmental threats to help ensure business continuity, slack can also be costly and reduce profitability. In this study we focus on operational slack, the form related to the firm's production processes. We investigate the role of operational slack on firm survival during its venture stage when its survival is significantly challenged by environmental threats. Specifically, we explore how change in three types of environmental uncertainty, namely dynamism, complexity, and lack of munificence, affect the relationship between operational slack and venture survival. Results suggest that with an increase in environmental uncertainty, operational slack lowers the likelihood of venture failure.     

A Method for Measuring Distance From a Training Data Set

A new method is proposed for measuring the distance between a training data set and a single, new observation. The novel distance measure reflects the expected squared prediction error when a quantitative response variable is predicted on the basis of the training data set using the distance weighted k-nearest-neighbor method. The simulation presented here shows that the distance measure correlates well with the true expected squared prediction error in practice. The distance measure can be applied, for example, in assessing the uncertainty of prediction.     

Obtaining a Trapezoidal Distribution

Given a most believed value for a quantity together with upper and lower possible deviations from that value, a rectangular distribution might be used to represent state-of-knowledge about the quantity. If the deviations are themselves known by probability distributions, and the value conditioned on the deviations is rectangular, then the marginal distribution of the value is determined by the distributions of the deviations. Here we show under quite general conditions that conversely, given the marginal distribution, the distributions of the deviations are uniquely determined. The case in which the marginal distribution is trapezoidal is studied in some detail.     

Analyzing Supersaturated Designs by Means of an Information Based Criterion

The cost and time consumption of many industrial experimentations can be reduced using the class of supersaturated designs since this can be used for screening out the important factors from a large set of potentially active variables. A supersaturated design is a design for which there are fewer runs than effects to be estimated. Although there exists a wide study of construction methods for supersaturated designs, their analysis methods are yet in an early research stage. In this article, we propose a method for analyzing data using a correlation-based measure, named as symmetrical uncertainty. This method combines measures from the information theory field and is used as the main idea of variable selection algorithms developed in data mining. In this work, the symmetrical uncertainty is used from another viewpoint in order to determine more directly the important factors. The specific method enables us to use supersaturated designs for analyzing data of generalized linear models for a Bernoulli response. We evaluate our method by using some of the existing supersaturated designs, obtained according to methods proposed by Tang and Wu (1997 Tang , B. , Wu , C. F. J. (1997). A method for constructing supersaturated designs and its E(s ²)-optimality. Canadian Journal of Statistics 25:191–201.[Crossref], [Web of Science ®] , [Google Scholar]) as well as by Koukouvinos et al. (2008 Koukouvinos , C. , Mylona , K. , Simos , D. E. ( 2008 ). E(s ²)-optimal and minimax-optimal cyclic supersaturated designs via multi-objective simulated annealing . Journal of Statistical Planning and Inference 138 : 1639 – 1646 .[Crossref], [Web of Science ®] , [Google Scholar]). The comparison is performed by some simulating experiments and the Type I and Type II error rates are calculated. Additionally, Receiver Operating Characteristics (ROC) curves methodology is applied as an additional statistical tool for performance evaluation.     

地缘政治风险的测度与经济效应分析

地缘政治风险日渐高企,冲击和影响着全球贸易与投资,构成左右全球经济复苏、政治格局演变和地缘关系重构的推力,也成为国内外国际政治、国际关系、国际经济等领域关注研究的前沿问题。通过梳理分析近些年地缘政治风险的经济效应,即地缘政治风险的技术创新效应、开放经济效应、经济增长效应等,试图为研究和制定相关政策提供研究脉络、研究内容、主要观点和前景展望等方面的一些有益启发。