语言多属性决策的目标规划模型

研究了只有部分属性权重信息、属性值以语言变量或不确定语言变量形式给出且决策者对方案有偏好信息的语言多属性决策问题.给出了语言变量和不确定语言变量的运算法则,以及不确定语言变量之间比较的可能度公式,定义了语言变量的偏离度概念.在属性值以1)语言变量和2)不确定语言变量,这两种形式给出的情形下,分别建立了一个基于偏离度的目标规划模型,并通过求解这两种模型分别获得相应的属性权重.然后对于情形1),利用语言加权平均(LWA)算子,对语言决策信息进行加权集成,继而对方案进行排序和择优;对于情形2),利用不确定语言加权平均(ULWA)算子,对不确定语言决策信息进行加权集成,并利用可能度公式构造可能度矩阵(互补判断矩阵),继而利用互补判断矩阵排序公式对决策方案进行排序和择优.最后进行了实例分析.     

The declining influence of family background on educational attainment in Australia: The role of measured and unmeasured influences

The paper examines changes in the influence of family background, including socioeconomic and social background variables on educational attainment in Australia for cohorts born between 1890 and 1982. We test hypotheses from modernization theory on sibling data using random effects models and find: (i) substantial declines in the influence of family background on educational attainment (indicated by the sibling intraclass correlations); (ii) declines in the effects of both economic and cultural socioeconomic background variables; (iii) changes in the effects of some social background variables (e.g., family size); (iv) and declines in the extent that socioeconomic and social background factors account for variation in educational attainment. Unmeasured family background factors are more important, and proportionally increasingly so, for educational attainment than the measured socioeconomic and social background factors analyzed. Fixed effects models showed steeper declines in the effects of socioeconomic background variables than in standard analyses suggesting that unmeasured family factors associated with socioeconomic background obscure the full extent of the decline.     

Unconditional analogues of Cochran–Mantel–Haenszel tests

The Cochran–Mantel–Haenszel tests are a suite of tests that are usually defined as conditional tests, tests that assume all marginal totals are known before sighting the data. Here unconditional analogues of these tests are defined for the more usual situation when the marginal totals are not known before sighting the data.     

不确定环境下的Supply-hub协同补货决策

个性化需求与零部件创新使得产品需求和补货提前期不确定,对供应链补货决策和运行成本产生重要影响。将提前期不确定因素引入Supply-hub协同补货研究中,探讨提前期随机和需求不确定情况下,考虑零部件配套性的三供应商单制造商生产两定制产品的Supply-hub协同补货决策问题;提出了三种补货策略,以供应链运行成本最小化为目标,建立不同策略下的供应链补货模型并求解最优补货批量和供应链最小运行成本;发现三种补货策略均存在唯一最优补货批量,基于Supply-hub的两种协同补货策略和基于分散决策的供应商独立补货策略各有优势,但基于Supply-hub的批量及时间协同的补货策略恒优于基于Supply-hub的集中补货策略。最后,通过MATLAB进行算例分析验证结论,发现基于Supply-hub的批量及时间协同的补货策略能有效降低需求不确定性带来的成本增加风险;通用件的提前期波动对于供应链期望运行成本的影响要高于定制件提前期波动的影响,因此在进行供应链补货策略选择时更加关注通用件提前期。     

Inference in Semi‐Parametric Dynamic Models for Repeated Count Data

This paper deals with a longitudinal semi‐parametric regression model in a generalised linear model setup for repeated count data collected from a large number of independent individuals. To accommodate the longitudinal correlations, we consider a dynamic model for repeated counts which has decaying auto‐correlations as the time lag increases between the repeated responses. The semi‐parametric regression function involved in the model contains a specified regression function in some suitable time‐dependent covariates and a non‐parametric function in some other time‐dependent covariates. As far as the inference is concerned, because the non‐parametric function is of secondary interest, we estimate this function consistently using the independence assumption‐based well‐known quasi‐likelihood approach. Next, the proposed longitudinal correlation structure and the estimate of the non‐parametric function are used to develop a semi‐parametric generalised quasi‐likelihood approach for consistent and efficient estimation of the regression effects in the parametric regression function. The finite sample performance of the proposed estimation approach is examined through an intensive simulation study based on both large and small samples. Both balanced and unbalanced cluster sizes are incorporated in the simulation study. The asymptotic performances of the estimators are given. The estimation methodology is illustrated by reanalysing the well‐known health care utilisation data consisting of counts of yearly visits to a physician by 180 individuals for four years and several important primary and secondary covariates.     

德国行政裁量制度探析

行政裁量制度是德国行政法学重点研究的理论之一,也是德国司法实务中的一个重大问题。其发展经历了从一开始的单一概念,逐渐产生要件裁量和效果裁量的分类。并且随着德国行政法学界对行政权控制研究的深入,衍生出不确定法律概念的独立体系及相应的约束机制。二次世界大战后德国行政法学界以宪法为依托,不断限缩行政裁量的概念和外延,从理论和司法实务两个层面论证了对行政裁量进行司法审查的可能性和必要性,从而形成了德国现在的从宪法、行政机关自身到司法机关的多层次的行政裁量法律控制体系。     

Automating argument construction

Over the past five years the Artificial Intelligence Center at SRI has been developing a new technology to address the problem of automated information management within real- world contexts. The result of this work is a body of techniques for automated reasoning from evidence that we call evidential reasoning. The techniques are based upon the mathematics of belief functions developed by Dempster and Shafer and have been successfully applied to a variety of problems including computer vision, multisensor integration, and intelligence analysis.

We have developed both a formal basis and a framework for implementating automated reasoning systems based upon these techniques. Both the formal and practical approach can be divided into four parts: (1) specifying a set of distinct propositional spaces, (2) specifying the interrelationships among these spaces, (3) representing bodies of evidence as belief distributions, and (4) establishing paths of the bodies for evidence to move through these spaces by means of evidential operations, eventually converging on spaces where the target questions can be answered. These steps specify a means for arguing from multiple bodies of evidence toward a particular (probabilistic) conclusion. Argument construction is the process by which such evidential analyses are constructed and is the analogue of constructing proof trees in a logical context.

This technology features the ability to reason from uncertain, incomplete, and occasionally inaccurate information based upon seven evidential operations: fusion, discounting, translation, projection, summarization, interpretation, and gisting. These operation are theoretically sound but have intuitive appeal as well.

In implementing this formal approach, we have found that evidential arguments can be represented as graphs. To support the construction, modification, and interrogation of evidential arguments, we have developed Gister. Gister provides an interactive, menu-driven, graphical interface that allows these graphical structures to be easily manipulated.

Our goal is to provide effective automated aids to domain experts for argument construction. Gister represents our first attempt at such an aid.     

Empirical Uncertain Bayes Methods in Area‐level Models

Random effects model can account for the lack of fitting a regression model and increase precision of estimating area‐level means. However, in case that the synthetic mean provides accurate estimates, the prior distribution may inflate an estimation error. Thus, it is desirable to consider the uncertain prior distribution, which is expressed as the mixture of a one‐point distribution and a proper prior distribution. In this paper, we develop an empirical Bayes approach for estimating area‐level means, using the uncertain prior distribution in the context of a natural exponential family, which we call the empirical uncertain Bayes (EUB) method. The regression model considered in this paper includes the Poisson‐gamma and the binomial‐beta, and the normal‐normal (Fay–Herriot) model, which are typically used in small area estimation. We obtain the estimators of hyperparameters based on the marginal likelihood by using a well‐known expectation‐maximization algorithm and propose the EUB estimators of area means. For risk evaluation of the EUB estimator, we derive a second‐order unbiased estimator of a conditional mean squared error by using some techniques of numerical calculation. Through simulation studies and real data applications, we evaluate a performance of the EUB estimator and compare it with the usual empirical Bayes estimator.     

不确定需求下考虑供应商参与机制的应急资源配置鲁棒优化研究

突发事件应急资源优化配置是突发事件发生后救援工作有效开展的前提和基本保障。本文在调研国内外相关研究的基础上，以应对地震灾难为背景研究考虑供应商参与机制的应急资源保障策略，在灾前选择供应商建立政府与供应商的合作机制完成政府储备仓库的选址与资源配置，突发事件发生后依托政府储备仓库和供应商生产能力共同满足应急救援对应急资源的分时段需求，以期协调供应商与政府储备、灾前实物采购与灾后生产能力采购的比例，在保障救援效率的同时降低应急资源保障体系的成本。同时由于地震灾难发生具有需求不确定性的特点，本文引入L1范数描述需求的不确定性，建立了备灾与灾害救援两阶段决策的鲁棒优化模型，并给出了鲁棒模型对应问题的转化方法。最后通过算例仿真验证了模型和对应问题转换方法的有效性，为地震的应对提供理论指导和决策支持。     

A General Multivariate Threshold GARCH Model With Dynamic Conditional Correlations

We introduce a new multivariate GARCH model with multivariate thresholds in conditional correlations and develop a two-step estimation procedure that is feasible in large dimensional applications. Optimal threshold functions are estimated endogenously from the data and the model conditional covariance matrix is ensured to be positive definite. We study the empirical performance of our model in two applications using U.S. stock and bond market data. In both applications our model has, in terms of statistical and economic significance, higher forecasting power than several other multivariate GARCH models for conditional correlations.