Understanding the Risk of an Avian Flu Pandemic: Rational Waiting or Precautionary Failure?

The precautionary principle (PP) has been proposed as the proper guide for the decision-making criteria to be adopted in the face of the new catastrophic risks that have arisen in the last decades. This article puts forward a workable definition of the PP based on the so-called alpha-maximin expected utility approach, applying it to the possible outbreak of the avian flu disease among humans. Moreover, it shows how the shortage and/or lack of effective drugs against the infection of the virus A(H5N1) among humans can be considered a precautionary failure.     

Assessment of supplier performance based on product-development strategy by applying multi-granularity linguistic term sets

Measuring supplier performance possesses the properties of multi-dimension and multi-scale, it increases the complexity of the aggregation and assessment process. A focal company must develop an effective procedure for overcoming the complexity of performance measurement. Furthermore, the assessment of supplier performance must conform to the product-developed strategy of the focal company. This study is a further research deeper into the concept already introduced in Chang et al. [1] [Applying fuzzy linguistic quantifier to select supply chain partners at different phases of product life cycle. International Journal of Production Economics 2006; 100(2):348–59]; using multi-granularity linguistic variable and numerical ration scale to represent the overall supply performance. By unifying the derived information, the measurement complexity could be resolved. The fuzzy preference was constructed to adjust the consistent direction and transform information into fuzzy relationship. Finally, fuzzy linguistic quantifier guided ordered weighted aggregation (FLQG-OWA) operator with maximal entropy was computed and aggregated with all indicators to meet the current policy of the focal company.     

多重随机环境下跨国采购和定价联合决策模型

在批发价、汇率和需求的三重随机波动环境下,考虑跨国采购与定价联合决策问题。本文主要利用随机过程来刻画批发价和汇率的随机性,并将两者的统计规律性纳入带有随机需求的决策模型的理论框架,进而给出跨国采购和定价联合决策模型及其可靠性评估机制。模型的相关结论表明:其一、不同周期的最优策略受到批发价与汇率波动的交互影响,当批发价和汇率波动性的重叠效应具有下降趋势时,销售商所采取的最优策略为增加一定的采购量,以实现系统的期望利润目标;其二、当批发价与汇率统计结构的属性为不可约遍历马氏链时,随机系统的下行风险具有良好的稳定性;其三、决策者可以通过本文提出靶向成本区间的上穿评估机制刻画随机系统的成本涨幅特征及其变化趋势,以解决供应商的最佳选择问题,从而达到了规避风险的运营目标。     

基于非参多元Expectile模型的原油价格风险测度研究—宏观不确定性视角

当下政治经济环境存在诸多不确定性,原油价格随着不确定性的增加而大幅波动,因此在当前不确定性环境中建立一个有效的风险预测模型具有重要的实际意义。本文基于非参多元Expectile模型,选取2010年1月5日至2020年1月6日的美国西德克萨斯原油价格的日度数据,构建同时包含地缘政治风险、经济政策不确定性等六个宏观不确定性变量的原油价格风险预测模型。此外,引入APARCH模型和基于蒙特卡罗方法的GARCH模型,比较以上三个模型预测能力。最后,基于预测的VaR值计算调整的Sharpe比率。结论表明,整体上,非参多元Expectile模型能较好处理多个宏观变量包含的信息,具有更高的预测能力。在不确定性事件叠加发生的时期预测表现依然优于其他模型,减少了不确定性增加导致原油市场波动幅度增加带来的风险,具有更强的稳定性。因此,在经济转型的关键时期,本研究可为政策制定者和监管当局面临不确定性上升环境下建立有效的原油价格风险预测模型提供参考,制定应对政策防范化解风险,同时也为投资者在当前复杂的国际形势下提供预测参考,尽量规避损失同时获取收益。     

相关多质量特性的优化设计

针对小样本情形下的相关多质量特性优化设计问题,在运用田口(Taguchi)质量损失函数度量多质量特性的稳健性基础上,本文提出了使用多变量偏最小二乘(Partial Least-Squares,PLS)回归模型处理此类问题的新方法,并结合实际的工业案例进行了分析.结果表明,本文所提出的新方法能够有效地处理相关多质量特性的优化设计问题.     

基于灰色关联度求解指标权重的改进方法

针对决策过程中指标权重的确定问题,在分析现有权重确定方法不足的基础上,提出了一种基于灰色关联度求解指标权重的改进方法,并对其性质进行了研究。该方法是对决策者给出的主观权重经验判断矩阵进行充分挖掘,提取出一个公共比较权重数列,并建立一个简易的数学模型,使确定的权重同时反映主观程度和客观程度。算例分析说明了该改进方法的简单性与实用性。     

级别不低于方法及其发展评述

级别不低于方法是一类解决多属性决策问题的重要方法.相对于其他方法力图建立可行方案集上的完全序.级别不低于方法所构建的是一种较弱的二元关系--级别不低于关系,它所要求的条件较弱,而得到的结果更为可靠.是近年来研究最为活跃、应用十分广泛的方法之一.本文将级别不低于方法划分为ELECTRE、PROMETHEE和PCCA等三大类分别进行了归纳和总结;介绍了近年来级别不低于方法的新发展,对级别不低于方法的公理化.不确定信息下的级别不低于方法以及多属性决策的敏感性分析和鲁棒性分析等问题给出了一些有意义的讨论.特别是对鲁棒性的定义和分析方法提出了一务切实可行的思路.     

Information preserving statistical obfuscation

The problem of limiting the disclosure of information gathered on a set of companies or individuals (the respondents) is considered, the aim being to provide useful information while preserving confidentiality of sensitive information. The paper proposes a method which explicitly preserves certain information contained in the data. The data are assumed to consist of two sets of information on each respondent: public data and specific survey data. It is assumed in this paper that both sets of data are liable to be released for a subset of respondents. However, the public data will be altered in some way to preserve confidentiality whereas the specific survey data is to be disclosed without alteration. The paper proposes a model based approach to this problem by utilizing the information contained in the sufficient statistics obtained from fitting a model to the public data by conditioning on the survey data. Deterministic and stochastic variants of the method are considered.     

COMPARISONS AND SELECTION OF TWO-PARAMETER EXPONENTIAL POPULATIONS

For two-parameter exponential populations with the same scale parameter (known or unknown) comparisons are made between the location parameters. This is done by constructing confidence intervals, which can then be used for selection procedures. Comparisons are made with a control, and with the (unknown) “best” or “worst” population. Emphasis is laid on finding approximations to the confidence so that calculations are simple and tables are not necessary. (Since we consider unequal sample sizes, tables for exact values would need to be extensive.)     

Optimal design of clinical trials comparing several treatments with a control

Clinical trials are often designed to compare several treatments with a common control arm in pairwise fashion. In this paper we study optimal designs for such studies, based on minimizing the total number of patients required to achieve a given level of power. A common approach when designing studies to compare several treatments with a control is to achieve the desired power for each individual pairwise treatment comparison. However, it is often more appropriate to characterize power in terms of the family of null hypotheses being tested, and to control the probability of rejecting all, or alternatively any, of these individual hypotheses. While all approaches lead to unbalanced designs with more patients allocated to the control arm, it is found that the optimal design and required number of patients can vary substantially depending on the chosen characterization of power. The methods make allowance for both continuous and binary outcomes and are illustrated with reference to two clinical trials, one involving multiple doses compared to placebo and the other involving combination therapy compared to mono-therapies. In one example a 55% reduction in sample size is achieved through an optimal design combined with the appropriate characterization of power.