Contrasting the Gini and Zenga indices of economic inequality

The current financial turbulence in Europe inspires and perhaps requires researchers to rethink how to measure incomes, wealth, and other parameters of interest to policy-makers and others. The noticeable increase in disparities between less and more fortunate individuals suggests that measures based upon comparing the incomes of less fortunate with the mean of the entire population may not be adequate. The classical Gini and related indices of economic inequality, however, are based exactly on such comparisons. It is because of this reason that in this paper we explore and contrast the classical Gini index with a new Zenga index, the latter being based on comparisons of the means of less and more fortunate sub-populations, irrespectively of the threshold that might be used to delineate the two sub-populations. The empirical part of the paper is based on the 2001 wave of the European Community Household Panel data set provided by EuroStat. Even though sample sizes appear to be large, we supplement the estimated Gini and Zenga indices with measures of variability in the form of normal, t-bootstrap, and bootstrap bias-corrected and accelerated confidence intervals.     

A Novel Human Error Probability Assessment Using Fuzzy Modeling

Human error is one of the significant factors contributing to accidents. Traditional human error probability (HEP) studies based on fuzzy number concepts are one of the contributions addressing such a problem. It is particularly useful under circumstances where the lack of data exists. However, the degree of the discriminability of such studies may be questioned when applied under circumstances where experts have adequate information and specific values can be determined in the abscissa of the membership function of linguistic terms, that is, the fuzzy data of each scenario considered are close to each other. In this article, a novel HEP assessment aimed at solving such a difficulty is proposed. Under the framework, the fuzzy data are equipped with linguistic terms and membership values. By establishing a rule base for data combination, followed by the defuzzification and HEP transformation processes, the HEP results can be acquired. The methodology is first examined using a test case consisting of three different scenarios of which the fuzzy data are close to each other. The results generated are compared with the outcomes produced from the traditional fuzzy HEP studies using the same test case. It is concluded that the methodology proposed in this study has a higher degree of the discriminability and is capable of providing more reasonable results. Furthermore, in situations where the lack of data exists, the proposed approach is also capable of providing the range of the HEP results based on different risk viewpoints arbitrarily established as illustrated using a real‐world example.     

一种榫卯连接方钢管组装框架模型的荷载 位移曲线试验研究

提出一种榫卯连接方钢管组装框架结构。对两个方向的平面框架模型进行受力性能试验。介绍试验概况，给出框架模型的竖向荷载与挠度和水平荷载与水平侧移曲线，这些曲线介于刚节点框架和铰节点框架之间，属于半刚性节点框架的范畴。     

General m-esttmators and applications to bounded influence estimation for non-linear regression

In this paper, we study the M-estimators in the case that λ_F:(β)=E_F:(φ(Z,β))=0 has more than one solution, We show that the numerical iterative procedures converge and that the resulting estimators are consistent and asymptotically normal. We apply them to the non-linear regression models, and then, we find an optimal M-estimate among those that have bounded gross error sensitivity.     

Asymptotic robustness of least median of squares for autoregressions with additive outliers

This paper considers the robustness properties in the time series context of the least median of squares (LMS) estimator. The influence function of the LMS estimator is derived under additive outlier contamination. This influence function is redescending and bounded for fixed values of the AR parameters. The gross-error sensitivity, however, is an unbounded function of the AR parameters. In order to asses the global robustness behavior of the LMS estimator, we consider several notions of breakdown. The breakdown points of the LMS estimator depend on the value of the underlying AR parameter. Generally, the breakdown point is below one half for high values of the AR parameter. The bias curves of the LMS estimator reveal, however, that the magnitude of outliers has to be considerable in order to cause breakdown.     

Further influence measures in factor analysis

Various influence measures are discussed for sensitivity analysis in factor analysis. The internal norm is used to characterize the vector-valued influence curves in factor analysis. Influence curves for the chi-square goodness of fit test, and the determinants of the model covariance matrix and unique variance matrix are derived. They are found to have simple formulas which are easy to be interpreted and have nice distributions for calibration. The likelihood displacement is also applied to sensitivity analysis in maximum likelihood factor analysis.     

ROC Curves in Non‐Parametric Location‐Scale Regression Models

Abstract. The receiver operating characteristic (ROC) curve is a tool of extensive use to analyse the discrimination capability of a diagnostic variable in medical studies. In certain situations, the presence of a covariate related to the diagnostic variable can increase the discriminating power of the ROC curve. In this article, we model the effect of the covariate over the diagnostic variable by means of non‐parametric location‐scale regression models. We propose a new non‐parametric estimator of the conditional ROC curve and study its asymptotic properties. We also present some simulations and an illustration to a data set concerning diagnosis of diabetes.     

模糊语义研究方法论纲

研究模糊语义必须以查德的“模糊集”理论作指导．运用现代语言学和现代语义学以及相关学科的研究成果来进行研究。这样也就使得研究方法具有多角度、多层次的特点，从而形成一个方法论系统：从整体方法上看，可实行宏观研究与微观分析相结合、定性研究与定量描述相结合、一般规律研究与特殊规律研究相结合的方法；从具体方法上看，应该注重模糊语义学的“综合性的边缘学科”属性，强调不同学科之间的渗透，融合各相关学科的理论和知识，来对模糊语义展开全面而深入的研究。     

自适应的Ad hoc MAC协议

为Adhoc网络提出了一种基于模糊逻辑的媒体接入控制层协议。该协议通过在MAC层采用模糊逻辑协调各个相互影响的数据流,为低优先级数据流选择附加退避窗口以减少其自身接入信道概率。通过这种方法,使得高优先级数据流在各种背景流量的条件下,均能够维持较高的端到端吞吐量和较低的端到端接入时延。仿真结果表明,该协议较802.11e协议更好地保护高优先级数据流的端到端时延和吞吐量。     

模糊车辆路径问题的一种混合遗传算法

在对模糊车辆路径问题进行简单描述的基础上,通过引入决策者主观偏好值的概念,给出了解决该问题的基本思路,建立了具有模糊特征的车辆路径问题的模糊机会规划模型,提出了求解该问题的一种基于模糊模拟的混合遗传算法。同时,在最小化总行驶距离的目标下,通过随机模拟方法研究了决策者主观偏好值的选择对最终决策目标的影响作用,并给出了其最佳取值范围。