Decision and choice in transforming data

Statistics are developed for predicting the effect of data transformations on the F statistic when the assumptions of homoscedasticity and normality underlying the AN OVA are not necessarily satisfied. These statistics are useful for determining whether and how to transform, They are developed by partitioning the change in the observed value of the jF-statistic under the transformation, into two expressions, one of which depends on the "truth" of HQ while the other does not. Using this partition, desirable properties are derived for transformations. Criteria are developed defining transformations which tend to preserve the type 1 error while increasing power when needed. Using these criteria, the notion of model robustness is introduced. It is shown that the Box-Cox methodology for selecting a power transform may, under certain conditions, produce a transformation which does not permit inferences to be made about the parent population from the transformed population. An alternative approach suggested here does permit such inferences.     

统计决策

一、统计决策的基本原理 (一)统计决策的意义和特点 决策是人们在一定条件下,为寻求优化目际和制定优化地达到目标的行动方案,而进行的一系列调查研究、对比选择工作。人们从事任何工作都关系着一系列的决策。决策的正确与否是工作能否顺利完成,预定目标能否顺利实现的关键。 决策包括两个方面的内容和过程:一是通过调查研究,制定出若干个可供选择的行动方案;二是通过比较鉴别,从若干个方案中进行优选,作出决策。     

信息、激励与统计决策

信息、激励与统计决策王国成为了认识和解决社会主义市场经济建设中出现的新的理论和实践问题,笔者曾撰文①探讨了市场经济条件下非对称信息的形成机理、统计特征和获取方法。继之,本文根据非对称信息较严格的定义,针对我国的具体情况,就非对称信息的分布类型及在激励...     

发展特色经济 加快西北地区经济发展

文章首先论证了发展特色经济是振兴西北经济的必然选择,然后从能源业、农业、高新技术产业、旅游业、现代生物与医药产业5个方面进行了总体构想,提出了发展特色经济的基本措施.     

Multiple Decision Procedures for Inference in Regression Models

We consider testing of the significance of the coefficients in the linear model. Unlike in the classical approach, there is no alternative hypothesis to accept when the null hypothesis is rejected. When there is a substantial deviation from the null hypothesis, we reject the null hypothesis and identify based on data alternative hypotheses associated with the independent variables or the levels that contributed most towards the deviation from the null hypothesis.     

Modelling and simulation to improve decision‐making in clinical development

Modelling and simulation are buzz words in clinical drug development. But is clinical trial simulation (CTS) really a revolutionary technique? There is not much more to CTS than applying standard methods of modelling, statistics and decision theory. However, doing this in a systematic way can mean a significant improvement in pharmaceutical research. This paper describes in simple examples how modelling could be used in clinical development. Four steps are identified: gathering relevant information about a drug and the disease; building a mathematical model; predicting the results of potential future trials; and optimizing clinical trials and the entire clinical programme. We discuss these steps and give a number of examples of model components, demonstrating that relatively unsophisticated models may also prove useful. We stress that modelling and simulation are decision tools and point out the benefits of integrating them with decision analysis. Copyright © 2005 John Wiley & Sons, Ltd.     

方案有限的多目标决策方法与资信评估

许多决策问题都有多个目标 ,在投资决策中对这种含有多目标方案间的选择就比单目标更复杂了 ,文章主要以资信评估来说明方案有限的多目标决策的具体方法及应用。     

完备决策表中的Bayes公式

文章就粗糙集与在完备的决策表中基于粗糙集建立起来的Bayes公式在决策分析上的应用进行了分析,得到它不仅相比主观的“古典”Bayes公式来得更为客观,而且它体现了所分析数据的概率结构与蕴涵和概率之间的紧密联系。     

Decision‐making in early clinical drug development

This paper illustrates an approach to setting the decision framework for a study in early clinical drug development. It shows how the criteria for a go and a stop decision are calculated based on pre‐specified target and lower reference values. The framework can lead to a three‐outcome approach by including a consider zone; this could enable smaller studies to be performed in early development, with other information either external to or within the study used to reach a go or stop decision. In this way, Phase I/II trials can be geared towards providing actionable decision‐making rather than the traditional focus on statistical significance. The example provided illustrates how the decision criteria were calculated for a Phase II study, including an interim analysis, and how the operating characteristics were assessed to ensure the decision criteria were robust. Copyright © 2016 John Wiley & Sons, Ltd.     

基于目标的风险型多属性群决策方法研究

在基于目标决策理论的基础上,分析决策者目标的不同类型及对应的目标效用函数,并针对决策者目标不同以及决策方案属性值为随机变量的风险型群决策问题,提出基于目标期望效用最大化的群体偏好集结方法.首先,该方法将属性的随机性、目标的随机性及决策者目标的满足程度转化为目标期望效用函数;其次,按期望效用类似的线性集结方式进行个体偏好的集结;最后,根据群体目标期望效用值形成方案排序.算例验证了该方法的有效性和实用性.     

The Role of Risk and Risk Aversion in an Individual's Migration Decision

Abstract

This paper proposes a simple, partial equilibrium model for studying an individual's migration decisions. It shows that an individual may choose to delay migration when the condition appears to be favorable, giving rise to the “waiting” behavior observed in the data. Using a closed-form solution, it also examines how the duration of the waiting is affected by a number of economic factors such as the risks associated with the wages in regions of origin and destination, the individual's attitude toward risk, etc.     

A Multiplicative Alo-group Based Hierarchical Decision Model and Application

Pairwise comparison matrix (PCM) is a popular technique used in multi-criteria decision making. The abelian linearly ordered group (alo-group) is a powerful tool for the discussion of PCMs. In this article, a criterion for acceptable consistency of PCM is introduced, which is independent of the scale and can be intuitively interpreted. The relation of the introduced criterion with the weak consistency is investigated. Then, a multiplicative alo-group based hierarchical decision model is proposed. The following approaches are included: (1) the introduced criterion for acceptable consistency is used to check whether or not a PCM is acceptable; (2) the row’s geometric mean method is used for deriving the local priorities of a multiplicative PCM; (3) a Hierarchy Composition Rule derived from the weighted mean is used for computing the criterion/subcriterion’s weights with regard to the total goal; and (4) the weighted geometric mean is used as the aggregation rule, where the alternative’s local priorities are min-normalized. The proposed model has the property of preserving rank. Moreover, it has counterparts in the additive case. Finally, the model is applied to a layout planning problem of an aircraft maintenance base with a computer-based software.     

企业经营决策离不开统计

企业要生存，经济要发展，管理要科学，需要的是大量的社会经济信息，而统计是社会经济信息的主体，随着现代企业制度的建立和现代化管理的发展，企业统计工作的任务，已从单纯的信息咨询、监督、服务等职能进一步向预测、监测和参与企业决策职能发展。统计在企业决策中的作用 1.统计信息是企业决策的基本依据。企业的生产经营决策必须以企业内部条件和外部环境为基本依据。统计工作不仅能及时、准确、全面、系统地反映企业内部生产经营活动的实际情况，而且还能搜集、整理与企业生产经营决策有关的企业外部环境的信息。通过对这些信息和…     

Tools for decision making under imprecise risk

Generalizing risk, imprecise risk is a situation where available objective information is expressible by a lower probability. We study properties of certain lower probabilities in metrizable spaces. Necessary and sufficient conditions are derived for stability of their cores under image and mixture, which are useful features in applying Expected Utility Theory under imprecise risk. Received: December 2000; revised version: March 2001     

Some aspects of decision making under uncertainty

Two discrete-time insurance models are studied in the framework of cost approach. The models being non-deterministic one deals with decision making under uncertainty. Three different situations are investigated: (1) underlying processes are stochastic however their probability distributions are given; (2) information concerning the distribution laws is incomplete; (3) nothing is known about the processes under consideration. Mathematical methods useful for establishing the (asymptotically) optimal control are demonstrated in each case. Algorithms for calculation of critical levels are proposed. Numerical results are presented as well.     

The Splitting Method for Decision Making

We show how a simple modification of the splitting method based on Gibbs sampler can be efficiently used for decision making in the sense that one can efficiently decide whether or not a given set of integer program constraints has at least one feasible solution. We also show how to incorporate the classic capture-recapture method into the splitting algorithm in order to obtain a low variance estimator for the counting quantity representing, say the number of feasible solutions on the set of the constraints of an integer program. We finally present numerical with with both, the decision making and the capture-recapture estimators and show their superiority as compared to the conventional one, while solving quite general decision making and counting ones, like the satisfiability problems.