区域协同创新能力的动态组合评价

文章针对多种动态评价方法评价结论非一致性问题,在Borda法的基础上,对不同相容动态评价方法的排序结果进行组合,提出基于Borda法的动态组合评价方法.构建区域协同创新能力评价指标体系,利用基于Borda法的动态组合评价方法对2009-2013年期间东部地区区域协同创新能力进行动态组合评价,评价结果表明:东部地区区域协同创新能力较稳定,北京区域协同创新能力最强,排名稳居第一;江苏和广东区域协同创新能力较强,排名前三;海南区域协同创新能力较弱,排名一直处于东部地区末位.     

服务企业竞争力组合的评价模型构建

文章构建了包含企业资源、企业能力和企业绩效三方面28个指标的服务企业竞争力评价指标体系，建立了服务企业竞争力组合评价模型。对单一评价模型结果运用KENDALL协和系数法方法进行事前相容性检验，建立平均值、Borda、Copeland和模糊Borda组合评价模型，运用Spearsman等级相关系数方法对组合评价结论进行事后一致性检验。输出最佳评价结果。     

城镇化水平评价指数体系构建与实证

文章以河南省18个主要城市为研究对象,首先根据河南省2011年底有关数据,分别利用综合指数、加权平均、主成分分析和因子分析法对河南省18个主要城市的城镇化水平进行评价和排序;其次,基于模糊Borda法建立组合评价模型,对18个主要城市的城镇化水平进行再评价,得到了更加客观、可行的评价结果,有效弥补了单一评价方法的不足,提高了评价结果的科学性、全面性;最后对评价结果进行分析,并提出提升河南省城镇化水平的措施。     

基于集对分析的组合评价方法

目前国内外提出的综合评价方法有几十种之多,如综合指数法、层次分析法、熵值法、主成分分析法等.这些方法可统称为单一评价法,单一评价法可分为两大类:主观赋权评价法和客观赋权评价法.前者如Delphi法、综合指数法等,后者如熵值法,主成分分析法等.评价方法不同在于评价者出发的角度不同,为了让评价的结果让人信服,有专家提出有必要选择多种方法进行评价,再将几种评价方法结果进行组合,这就是所谓的组合评价方法.     

几种组合评价法及其应用分析

文章提出了几种组合评价法,分析在应用中应采取的计算步骤,为了保证组合评价结论的合理性和科学性,着重分析了运用该方法时必须进行事前检验和事后检验。用中国高校排行榜对这几种组合评价法做实例分析,对事前检验和事后检验分别作了计算,并将几种组合评价法作了粗略比较。     

基于Borda法不确定偏好序下的双边匹配决策模型

针对不确定偏好序下的双边匹配决策问题,提出了一种决策方法。首先,对具有不确定偏好序信息的双边匹配决策问题进行了描述,依据传统Borda法的思想,针对不确定偏好序的特点构建Borda分值计算规则;然后,基于综合Borda分值给出了满意度测度方法,在此基础上,建立双边满意匹配优化模型,求解模型获得双边匹配方案;最后,通过算例验证了提出方法的可行性和有效性。     

组合评价法研究

组合评价法是近年来发展起来的一类综合评价方法。在分析单一综合评价法的基础上,本文引入了组合评价法,详细阐述了目前国内文献中出现的各种组合方法,对组合评价法的优点和缺点作了总结,并提出了对组合评价法的几点看法。     

基于熵值法与理想点法的上市公司财务状况分析的实证研究

文章建立了上市公司财务状况综合评价指标体系,详细介绍了熵值法和理想点法两种评价模型,并通过实际数据进行了实证分析,最后采用综合序数法将两种方法的评价结果组合起来得到一个最终的评价结果。     

基于组合评价的浙江省城市可持续发展能力实证分析

通过构建层次分析法、熵权法及主成分分析的组合评价模型,对浙江省十一个地级市的可持续发展能力进行综合评价。结果显示,杭州市毫无争议的登上"头把交椅",而其他地级市也有其相应的"座次"。同时,也可以看出采用三种评价方法对城市可持续发展能力的评价结果有所不同,但三者之间总体上具有高度的正相关性。因此,采用这三种评价方法为基础的组合评价模型是合理有效的。     

基于语言评价信息视角的PSS产品开发方案决策评价

文章以语言信息评价为切入点对PSS方案决策评价方法进行了研究,提出了将定量评价信息与定性评价信息相融合的系统化决策模型体系.通过将语言变量模糊化与定量评价指标无量纲化将定量与定性语言评价指标相集成,形成聚合评价模糊数,最后在Bass-Kwakernaak排序法的基础上运用Borda函数得出方案最终排序.案例证明了该方法的有效性.     

基于改进熵值法的西部地区城市化水平综合评价研究

从广义城市化的内涵出发,构建了融人口、经济、社会文化和城市建设于一体的城市化水平评价指标体系,采用改进的熵值法,对西部12个省区的城市化水平给予了综合评价,并对其2003-2005年的城市化水平进行综合排序,用以找出各省区的优势和差距,便于针对性地制定提高城市化水平的对策。     

贫困测度指标及其评价

一、引言一般来说,研究贫困问题主要涉及三个方面:一是贫困的识别;二是贫困程度测定;三是反贫困效果判定以及相应的战略选择。贫困识别问题主要指贫困的基本范畴及贫困线的合理确定,关系到贫困集合的准确界定;贫困程度的测定主要指贫困指数的定义和计算,关系到贫困程度大小的判     

企业集团风险形成机理与预警研究

文章首先对企业集团风险进行辨识,并对风险所形成的机理进行了分析。其研究思路主要从方法着手,通过对集团风险指标体系的建立、筛选与评价方法,以及对集团风险预警信号系统和集团风险预警模型的建立,对集团所面临的风险进行了综合测评。应用预警信号系统和模糊综合评价法对集团进行了定量、定性预警。     

COWORDS: a probabilistic model for multiple word clouds

Word clouds constitute one of the most popular statistical tools for the visual analysis of text documents because they provide users with a quick and intuitive understanding of the content. Despite their popularity for visualizing single documents, word clouds are not appropriate to compare different text documents. Independently generating word clouds for each document leads to configurations where the same word is typically located in widely different positions. This makes it very difficult to compare two or more word clouds. This paper introduces COWORDS, a new stochastic algorithm to create multiple word clouds, including one for each document. The shared words in multiple documents are placed in the same position in all clouds. Similar documents produce similar and compact clouds, making it easier to simultaneously compare and interpret several word clouds. The algorithm is based on a probability distribution in which the most probable configurations are those with a desirable visual aspect, such as a low value for the total distance between the words in all clouds. The algorithm output is a set of word clouds that are randomly selected from this probability distribution. The selection procedure uses a Markov chain Monte Carlo simulation method. We present several examples that illustrate the performance and visual results that can be obtained by our algorithm.     

Advances in estimation by the item sum technique using auxiliary information in complex surveys

To collect sensitive data, survey statisticians have designed many strategies to reduce nonresponse rates and social desirability response bias. In recent years, the item count technique has gained considerable popularity and credibility as an alternative mode of indirect questioning survey, and several variants of this technique have been proposed as new needs and challenges arise. The item sum technique (IST), which was introduced by Chaudhuri and Christofides (Indirect questioning in sample surveys, Springer-Verlag, Berlin, 2013) and Trappmann et al. (J Surv Stat Methodol 2:58–77, 2014), is one such variant, used to estimate the mean of a sensitive quantitative variable. In this approach, sampled units are asked to respond to a two-list of items containing a sensitive question related to the study variable and various innocuous, nonsensitive, questions. To the best of our knowledge, very few theoretical and applied papers have addressed the IST. In this article, therefore, we present certain methodological advances as a contribution to appraising the use of the IST in real-world surveys. In particular, we employ a generic sampling design to examine the problem of how to improve the estimates of the sensitive mean when auxiliary information on the population under study is available and is used at the design and estimation stages. A Horvitz–Thompson-type estimator and a calibration-type estimator are proposed and their efficiency is evaluated by means of an extensive simulation study. Using simulation experiments, we show that estimates obtained by the IST are nearly equivalent to those obtained using “true data” and that in general they outperform the estimates provided by a competitive randomized response method. Moreover, variance estimation may be considered satisfactory. These results open up new perspectives for academics, researchers and survey practitioners and could justify the use of the IST as a valid alternative to traditional direct questioning survey modes.     

熵值法在EXCEL中的VBA实现

熵值法是多指标综合评价中根据指标数据提供的信息量对指标进行客观赋权的一种方法.但该方法的数据处理过程较为复杂。本文利用VBA(VisualBasictbrApplication)在EXCEL下编写宏程序,使用户处理数据时彻底从手工操作中解放出来,最终达到熵值法在EXCEL中实现“傻瓜”操作的目标。     

国际上对国家统计机构的综合比较及其评价

自20世纪80年代以来,随着信息技术的迅猛发展,一些国家的统计机构面临着国内外变化的巨大压力。一方面,认为计算机网络技术的应用普及,国家统计机构应相应减少经费开支和统计人员数量,减轻社会统计调查负担。例如,北欧一些国家政府提出削减统计预算支出政策,国家统计机构面临着提高统计工作运行效率的内部压力。另一方面,全球经济一体化进程的加快,使得视作国家统计机构生命的统计数据质量日益受到国内外政府和有关组织的高度重视,特别是在墨西哥、亚洲金融危机之后。国际社会普遍认为,统计数据失真、数据不完整、公布不及时、对社会需求反…     

新浪微博社会网络的自组织行为研究

互联网社会网络主要用于信息传播与共享,这种行为的自组织性主要体现在信息传播。根据自组织理论,新浪微博社会网络是一个自组织系统,从整体网络、个体网络、小团体、小世界效应构建模型,并以"可持续发展"话题为例,采用"滚雪球抽样方法",考虑网络用户间的"发布、转发、评论、@、回复"关系,进行实证研究。结果表明:社会网络存在自组织行为;整体自组织现象弱,局部明显;由于网络用户角色不同,围绕网络用户形成的自组织网络凝聚强度不同。     

Distance sampling methodology

We consider the method of distance sampling described by Buckland, Anderson, Burnham and Laake in 1993. We explore the properties of the methodology in simple cases chosen to allow direct and accessible comparisons of distance sampling in the design- and model-based frameworks. In particular, we obtain expressions for the bias and variance of the distance sampling estimator of object density and for the expected value of the recommended analytic variance estimator within each framework. These results enable us to clarify aspects of the performance of the methodology which may be of interest to users and potential users of distance sampling.     

New Developments in Statistical Computing

Many users of regression methods are attracted to the notion that it would be valuable to determine the relative importance of independent variables. This article demonstrates a method based on hierarchies that builds on previous efforts to decompose R ² through incremental partitioning. The standard method of incremental partitioning has been to follow one order among the many possible orders available. By taking a hierarchical approach in which all orders of variables are used, the average independent contribution of a variable is obtained and an exact partitioning results. Much the same logic is used to divide the joint effect of a variable. The method is general and applicable to all regression methods, including ordinary least squares, logistic, probit, and log-linear regression. A validation test demonstrates that the algorithm is sensitive to the relationships in the data rather than the proportion of variability accounted for by the statistical model used.