Multivariate outlier detection in incomplete survey data: the epidemic algorithm and transformed rank correlations

Summary.  As a part of the EUREDIT project new methods to detect multivariate outliers in incomplete survey data have been developed. These methods are the first to work with sampling weights and to be able to cope with missing values. Two of these methods are presented here. The epidemic algorithm simulates the propagation of a disease through a population and uses extreme infection times to find outlying observations. Transformed rank correlations are robust estimates of the centre and the scatter of the data. They use a geometric transformation that is based on the rank correlation matrix. The estimates are used to define a Mahalanobis distance that reveals outliers. The two methods are applied to a small data set and to one of the evaluation data sets of the EUREDIT project.     

专业观众展览会参观动机研究——来自东莞的证据

以展览业发达的东莞为研究样地,利用因素分析与聚类研究相结合的综合定量方法,对专业观众的观展动机进行综合评估及分类研究。研究表明,专业观众的非购买动机甚过购买动机,他们观展动机的四个维度因子依次为:搜集信息、建立市场关系、考察奖励、采购行为。本研究还发现专业观众的观展动机分为目标模糊型、信息搜集导向型、目标多维明确型三种类型。     

基于移动代理的新型IDS维护更新机制设计

提出了一种基于移动代理的新型分布式入侵检测系统。该系统是针对广域网环境专门设计的,数据的处理通过各节点所设置的代理来进行分布式计算,不仅能实现全网络范围内的入侵检测功能,具有良好的可移植性;而且对网络系统和主机的资源占用较低,减少了出现网络瓶颈的可能。还建立了移动代理的新型分布式入侵检测系统的体系结构和理论分析模型,并讨论了该系统的维护更新机制。     

CCD图象检测信号的失真校正

本文从CCD图象输入系统误差引起图象检测信号失真的原因分析出发,以降低系统装校误差精度要求和增大元器件离散性的宽容度为目标,讨论朱真校正方法的原理和数学描述。最后,介绍两种失真校正方法。     

A simple estimator for a shared frailty regression model

Summary. We propose a simple estimation procedure for a proportional hazards frailty regression model for clustered survival data in which the dependence is generated by a positive stable distribution. Inferences for the frailty parameter can be obtained by using output from Cox regression analyses. The computational burden is substantially less than that of the other approaches to estimation. The large sample behaviour of the estimator is studied and simulations show that the approximations are appropriate for use with realistic sample sizes. The methods are motivated by studies of familial associations in the natural history of diseases. Their practical utility is illustrated with sib pair data from Beaver Dam, Wisconsin.     

横向塞曼稳频He－Ne激光器的研究

稳频横向塞曼Ｈｅ－Ｎｅ激光器作为一种新型光源，具有功率大、频差低、易于相位细分的特点，因而能广泛应用于各种精密测量中．本文介绍了我们研制的稳频横向塞曼激光器，实验结果表明，其激光频率稳定度达４．７×１０（－１０），再现性达１．８×１０（－８）．     

产业集群:提升天津滨海新区竞争力的战略选择

产业集群的研究已经成为地区或国家竞争力研究以及区域经济研究的热点.在发达国家,基于产业集群而形成的集群经济早已成为区域经济的重要板块和亮点.本文通过对产业集群理论的回顾以及对产业集群竞争优势的研究,深入思考天津滨海新区所特有的经济条件和发展优势,提出了为提升区域竞争力、加快实施产业集群的经济发展战略.     

互联网环境下学术期刊防范学术不端行为技术研究

利用互联网环境，从技术的角度出发，对一稿多投、抄袭行为、剽窃行为以及捏造行为等学术不端行为的检测与防范进行研究，提出了各种操作上可行的方法。实践证明，运用这些方法，可有效地防范有学术不端行为的文章在学术期刊上发表。     

Outlier detection in high-dimensional regression model

An outlier is defined as an observation that is significantly different from the others in its dataset. In high-dimensional regression analysis, datasets often contain a portion of outliers. It is important to identify and eliminate the outliers for fitting a model to a dataset. In this paper, a novel outlier detection method is proposed for high-dimensional regression problems. The leave-one-out idea is utilized to construct a novel outlier detection measure based on distance correlation, and then an outlier detection procedure is proposed. The proposed method enjoys several advantages. First, the outlier detection measure can be simply calculated, and the detection procedure works efficiently even for high-dimensional regression data. Moreover, it can deal with a general regression, which does not require specification of a linear regression model. Finally, simulation studies show that the proposed method behaves well for detecting outliers in high-dimensional regression model and performs better than some other competing methods.     

Do individuals successfully cover up their lies? Evidence from a compliance experiment

We study how well individuals in a face-to-face situation can delude others. We exploit data from a laboratory experiment in which participants were asked to assess video-taped statements as being rather truthful or untruthful. The statements are face-to-face tax declarations. The video clips feature each subject twice making the same declaration: One time the subject is reporting honestly, and the other time willingly dishonestly. This allows us to investigate within-subject differences in perceived truthfulness. Our study provides several novel insights. We find that individuals can cover up their lies successfully. On average, a subject is perceived as more truthful if she deceives than if she reports honestly. In particular, individuals with a genuine dishonest appearance manage to increase their perceived truthfulness by up to 14 percent when lying. Moreover, our results show that a subject appears less truthful if she had previously been caught lying. Being detected as a liar previously appears to impair self-confidence and to thereby lower an individual’s ability to deceive.