Bayesian validation assessment of multivariate computational models

Multivariate model validation is a complex decision-making problem involving comparison of multiple correlated quantities, based upon the available information and prior knowledge. This paper presents a Bayesian risk-based decision method for validation assessment of multivariate predictive models under uncertainty. A generalized likelihood ratio is derived as a quantitative validation metric based on Bayes’ theorem and Gaussian distribution assumption of errors between validation data and model prediction. The multivariate model is then assessed based on the comparison of the likelihood ratio with a Bayesian decision threshold, a function of the decision costs and prior of each hypothesis. The probability density function of the likelihood ratio is constructed using the statistics of multiple response quantities and Monte Carlo simulation. The proposed methodology is implemented in the validation of a transient heat conduction model, using a multivariate data set from experiments. The Bayesian methodology provides a quantitative approach to facilitate rational decisions in multivariate model assessment under uncertainty.     

Ranking Nuclear and Radiological Terrorism Scenarios: The Italian Case

A quantitative criterion for ranking the different scenarios of nuclear and radiological terrorism has been developed. The aim of the model is not to predict terroristic events but only to indicate which scenario has the higher utility from the point of view of a terroristic organization in terms of balance between factors favoring and discouraging the attack, respectively. All these factors were quantified according to a scoring system that takes into account the logarithmic relationship between perceptions and stimuli. The criterion was applied to several scenarios, each of which was modeled in a simple but not trivial way in order to estimate the expected damage in terms of probable life losses from both radiative and nonradiative effects. The outcome from the ranking method indicates that the attractive scenario appears to be the detonation of a low yield improvised nuclear device in the metropolitan area of a major city.     

高校内部审计风险原因及对策研究

内部审计机构的相对独立性、审计人员业务能力的局限性、审计方法及审计手段的落后状况等因素决定了内部审计风险的客观存在,目前高校办学和业务活动出现了一些新的特点,高校的内部审计工作不仅同样也存在风险,且较之以前有加大的趋势。本文论述了高校内部审计风险产生原因并相应提出了防范和控制风险的措施。     

对北光集团加强子公司财务管理的案例分析

随着市场经济的建立与发展,企业所有制形式和组织结构发生了巨大的变化,特别是规模化企业集团得到了迅猛发展。近年来,在企业集团的各子公司财务管理中发现了一些不容忽视的问题,本文从北光集团的实际情况出发,分析了目前北光集团对子公司实施财务管理中的成绩及不足,并提出了北光集团加强对子公司财务管理的改进措施。     

Goodness‐of‐fit methods for matched case‐control studies

The authors propose graphical and numerical methods for checking the adequacy of the logistic regression model for matched case‐control data. Their approach is based on the cumulative sum of residuals over the covariate or linear predictor. Under the assumed model, the cumulative residual process converges weakly to a centered Gaussian limit whose distribution can be approximated via computer simulation. The observed cumulative residual pattern can then be compared both visually and analytically to a certain number of simulated realizations of the approximate limiting process under the null hypothesis. The proposed techniques allow one to check the functional form of each covariate, the logistic link function as well as the overall model adequacy. The authors assess the performance of the proposed methods through simulation studies and illustrate them using data from a cardiovascular study.     

关于有限群的超可解性

利用弱拟正规和广义中心元概念得到有限群为超可解群的若干充要条件,推广了现有的结果.     

Loss functions for estimation of extrema with an application to disease mapping

It is often of interest to find the maximum or near maxima among a set of vector‐valued parameters in a statistical model; in the case of disease mapping, for example, these correspond to relative‐risk “hotspots” where public‐health intervention may be needed. The general problem is one of estimating nonlinear functions of the ensemble of relative risks, but biased estimates result if posterior means are simply substituted into these nonlinear functions. The authors obtain better estimates of extrema from a new, weighted ranks squared error loss function. The derivation of these Bayes estimators assumes a hidden‐Markov random‐field model for relative risks, and their behaviour is illustrated with real and simulated data.     

Modeling External Risks in Project Management

To ascertain the viability of a project, undertake resource allocation, take part in bidding processes, and other related decisions, modern project management requires forecasting techniques for cost, duration, and performance of a project, not only under normal circumstances, but also under external events that might abruptly change the status quo. We provide a Bayesian framework that provides a global forecast of a project's performance. We aim at predicting the probabilities and impacts of a set of potential scenarios caused by combinations of disruptive events, and using this information to deal with project management issues. To introduce the methodology, we focus on a project's cost, but the ideas equally apply to project duration or performance forecasting. We illustrate our approach with an example based on a real case study involving estimation of the uncertainty in project cost while bidding for a contract.     

合作学习在大学英语教学中的应用

由美国一些教育家倡导的合作学习是以学生为中心的教学方法,适合外语学习的特点,在世界上许多国家推广.将合作学习的方法灵活地应用于大学英语教学,不仅能够提高非英语专业学生的英语听说能力,营造良好的课堂气氛,还能够培养学生的学习自主性和人际交往能力.     

银行个人住房抵押贷款预警系统构想

在分析银行住房抵押贷款的各种风险因素的基础之上，提出模糊预警模型，给出预警结果。