一个新的银行信用风险评估方法

本文以银行信用风险管理为例,将粗糙集和决策树两种具有互补优势的数据挖掘方法相结合,对客户信用做出归类分析判断,最后利用决策树生成决策规则.实践证明,这种方法忠于原始数据,提高了分类准确度,减小了决策树规模,具有良好的性能.     

Reviews

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Bayesian analysis of dynamic magnetic resonance breast images

Summary.  We describe an integrated methodology for analysing dynamic magnetic resonance images of the breast. The problems that motivate this methodology arise from a collaborative study with a tumour institute. The methods are developed within the Bayesian framework and comprise image restoration and classification steps. Two different approaches are proposed for the restoration. Bayesian inference is performed by means of Markov chain Monte Carlo algorithms. We make use of a Metropolis algorithm with a specially chosen proposal distribution that performs better than more commonly used proposals. The classification step is based on a few attribute images yielded by the restoration step that describe the essential features of the contrast agent variation over time. Procedures for hyperparameter estimation are provided, so making our method automatic. The results show the potential of the methodology to extract useful information from acquired dynamic magnetic resonance imaging data about tumour morphology and internal pathophysiological features.     

凉山谚语汇列及特点（一）

本文收集凉山谚语,并且分类列出。     

Measurement error evaluation of self-reported drug use: a latent class analysis of the US National Household Survey on Drug Abuse

Summary. Latent class analysis (LCA) is a statistical tool for evaluating the error in categorical data when two or more repeated measurements of the same survey variable are available. This paper illustrates an application of LCA for evaluating the error in self-reports of drug use using data from the 1994, 1995 and 1996 implementations of the US National Household Survey on Drug Abuse. In our application, the LCA approach is used for estimating classification errors which in turn leads to identifying problems with the questionnaire and adjusting estimates of prevalence of drug use for classification error bias. Some problems in using LCA when the indicators of the use of a particular drug are embedded in a single survey questionnaire, as in the National Household Survey on Drug Abuse, are also discussed.     

分享经济核算需要厘清的几个基本问题

分享经济作为一种新兴经济,社会各界对其认知存在显著差异,导致有关核算研究及统计实践面临诸如定义、生产范围界定、统计分类、估价和增加值估算等问题。为此,本文立足于理论与实 践的角度,结合各方面研究归纳出分享经济的本质,一种有偿暂时性让渡闲置资源使用权的市场性分享 活动,这种活动在互联网通信技术,尤其是分享平台的助力下,进入了规模化发展阶段。同时,利用SNA的生产观点归纳出分享经济的生产与产出统计范围,并对相关统计分类方法和标准进行了探讨。最后,针对分享经济估价问题提出了有关估算方法。 本文的创新在于提出了分享经济活动的理论边界,明确了分享经济核算研究的主体及统计范围,有助于解决统计实践中产品与行业活动“统不进、分不开”的问题,为完善“三新”统计制度提供了参考依据。     

一种加权主成分距离的聚类分析方法

指标之间的高度相关性及其重要性差异导致了传统聚类分析方法往往无法获得良好的分类效果。本文在对传统聚类分析方法及其各种改进方法局限性展开探讨的基础上,运用数学方法重构了分类定义中的距离概念,通过定义自适应赋权的主成分距离为分类统计量,提出一种新的改进的主成分聚类分析方法——加权主成分距离聚类分析法。理论研究表明,加权主成分距离聚类分析法系统集成了已有聚类分析方法的优点,有充分的理论基础保证其科学合理性。仿真实验结果显示,加权主成分距离聚类分析法能够有效解决已有聚类分析方法在特定情形下的失真问题,所得分类效果更为理想。     

The Role of Classification Trees and Expert Knowledge in Building Bayesian Networks: A Case Study in Medicine

In clinical research an early and prompt detection of the risk class of a new patient may really play a crucial role in determining the effectiveness of the treatment and, consequently, achieving a satisfying prognosis of the patient's chances. There exists a number of popular rule-based algorithms for classification, whose performances are very attractive whenever data of large number of patients are available. However, when datasets only include data of a few hundred patients, the most common approaches give unstable results and developing effective decision-support systems become scientifically challenging. Since rules can be derived from different models as well as expert knowledge resources, each of them having its advantages and weaknesses, this article suggests a “hybrid” approach to address the classification problem when the number of patients is too small to effectively use a single technique only. The hybrid strategy was applied to a case study and its predictive performance was compared with performances of each single approach: due to the seriousness of a misclassification of high-risk patients, special attention was paid on the specificity. The results show that the hybrid strategy outperforms each single strategy involved.     

ISCED（2011）：理论发展与分类变化

ISCED（2011）是联合国教科文组织（UNESCO）即将在全球实施的一套新的教育统计国际标准。本文分析了ISCED（2011）教育理论和分类方法的重要变化：教育理论方面,修订了教育概念、强调了非正规教育、确认了公认资格证书在教育活动中的作用、突出了高等教育的多样化;分类方法方面,构建了双变量交叉分类的框架、建立了受教育程度的分类、对教育等级分类进行了改进、采用了三级编码方法。论文最后指出,我国应在教育路径多元化、高等教育多样化、终身教育等方面予以借鉴。     

Goodness of Fit Statistics for the Exponential Distribution When the Data Are Grouped

Abstract

In many industrial and biological experiments, the recorded data consist of the number of observations falling in an interval. In this paper, we develop two test statistics to test whether the grouped observations come from an exponential distribution. Following the procedure of Damianou and Kemp (Damianou, C., Kemp, A. W. (1990 Damianou, C. and Kemp, A. W. 1990. New goodness of statistics for discrete and continuous data. American Journal of Mathematical and Management Sciences, 10: 275–307. [Taylor & Francis Online] , [Google Scholar]). New goodness of statistics for discrete and continuous data. American Journal of Mathematical and Management Sciences 10:275–307.), Kolmogrov–Smirnov type statistics are developed with the maximum likelihood estimator of the scale parameter substituted for the true unknown scale. The asymptotic theory for both the statistics is studied and power studies carried out via simulations.