湖南省各市州经济发展水平评价

本文利用主成分分析法分析了湖南各市州的经济发展水平和经济综合实力,对湖南省14个市州的经济发展情况做出综合评价,得出了各市州在湖南省的经济地位.最后用系统聚类分析法进行了验证,结果表明用多元统计分析法来评价地区经济发展水平是可行的.     

安徽省各地市企业科技开发情况分析

本文应用主成份分析法和聚类方法，对安徽省各地市企业科技开发状况进行了分析。通过定量分析表明，安徽省各地区科技开发水平差距较大，其现状应引起有关部门的重视。     

湖南省公共医疗卫生支出效率及其影响因素实证分析

利用DEA-Tobit两阶段分析法,计算出2009-2013年5年间湖南省14个地级市政府公共医疗卫生支出的综合技术效率值、纯技术效率值、规模效率值三种效率值,分析出湖南省各地级市政府公共医疗卫生支出所处规模报酬阶段,并对反映卫生支出资金配置的综合技术效率水平的外部影响因素加以回归分析.结果发现:湖南省各地区公共医疗卫生效率水平整体水平偏低并且存在明显的差异性,除长沙以外的其他地级市政府公共医疗卫生支出均处于不同程度的非充分效率水平.湖南省各地区人均生产总值及城市化水平对公共医疗卫生支出效率有显著的促进作用.教育水平、人口密度、居民人均可支配收入对湖南省公共医疗卫生支出效率的提高有阻碍作用.     

企业信息资源配置的模糊综合评价

建立了综合评价企业信息资源配置水平的指标体系，采用层次分析法确定指标体系的权重，使用模糊评价方法评价企业的信息资源配置水平，并结合实例作了说明。     

基于AHP和模糊综合评判的生活垃圾处理模式评价

城市生活垃圾的科学处理,对城市的生态环境和居民的身心健康有着重大意义.以保定市新建的白沟综合垃圾处理厂为研究对象,选取经济、技术、环境、社会四大类指标,每个一级指标下设立多个二级指标,共选取了14个指标因子进行评价,利用层次分析法(AHP)和模糊综合评价方法对4种生活垃圾处理技术进行分析.结果表明,最适合保定白沟垃圾处理厂建设的垃圾处理方式为综合处理法.     

基于AHP的模糊综合评价模型在居民幸福指数评测中的应用

针对居民幸福指数展开社会调研,依据调研数据,构建保定市居民幸福指数评价指标体系,运用基于层次分析法(AHP)的模糊综合评价模型,形成较为科学、完善的评估系统,使评价方法及结果更趋合理,并为政府职能部门进一步加快经济建设、促进社会和谐发展提供必要的理论保障.     

我国各省(市、自治区)高技术产业发展水平因子分析与综合评价

建立了高技术产业发展水平的综合评价指标体系,采用主成分因子分析法进行了有效降维,得出了衡量高技术产业发展水平的四个公共因子,构建了相应的客观加权的综合评价模型.通过对31个省(市、自治区)的定量分析,发现了我国高技术产业在东西部发展不均衡,在东部地区尤其是珠江三角洲、长江三角洲、环渤海地区显示出明显优势的特点,这与我国实情吻合甚好.最后,根据因子得分分布图将31个省(市、自治区)分成了10类,分类提出了如何加速高技术产业发展的建议.     

基于层次分析法可拓学的小城市公交服务评价

从基础设施服务和企业运营服务两方面,构建适合于小城市公共交通服务评价的指标体系,运用层次分析法确定指标的权重系数.根据可拓学理论构造经典域、节域和关联函数,建立小城市公共交通服务的层次分析法-可拓学的综合评价模型,并以江苏省泰州市公交为例,验证模型的实用性.     

新疆区域人力资本配置对经济增长的影响研究

1999年,党中央提出并实施"西部大开发"战略.2010年以来,党中央再次号召全国19个省市援疆.值此难得的重要战略机遇期,加大人力资本区域配置对经济增长影响的研究,对于实现新疆经济社会又好又快地发展具有重要的意义.使用变系数面板模型,计算各地州人力资本、物质资本对经济增长的贡献,并提出优化区域人力资本配置的对策建议.最终得出的基本结论:物质资本和人力资本对各地州经济增长有显著的积极作用,总体上看,经济发展水平较高的地州,其物质资本对经济增长的拉动作用强于经济发展水平较低的地州,而其人力资本对经济增长的拉动作用弱于经济发展水平较低的地州.     

基于AHP-GRA的湖北省科技创新人才开发评价研究

科技创新人才是推动经济社会发展的核心资源,是提升一个区域乃至一个国家核心竞争力的关键所在.以科技创新人才开发为核心,从人才可持续发展的视角,建立一套衡量湖北省科技创新人才开发水平的评价指标体系,同时结合层次分析法(AHP)和灰色关联分析法(GRA)构建评价模型,对湖北省科技创新人才开发水平及发展态势进行实证分析,探索提高湖北省科技创新人才开发水平的对策建议,为湖北省制定科技人才开发战略以及加强科技人才队伍建设提供决策参考.     

Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA

This study surveys the increasing research field of performance measurement by making use of a bibliometric literature analysis. We concentrate on two approaches, namely Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) as the most important methods to evaluate the efficiency of individual and organizational performance. It is the first literature survey that analyses DEA and SFA publications jointly, covering contributions published in journals, indexed by the Web of Science database from 1978 to 2012. Our aim is to identify seminal papers, playing a major role in DEA and SFA development and to determine areas of adoption. We recognized a constant growth of publications during the years identifying DEA as a standard technique in Operations Research, whereas SFA is mainly adopted in Economic research fields. Making use of document co-citation analysis we identify Airports and Supplier Selection (DEA) as well as Banking and Agriculture (SFA) as most influential application areas. Furthermore, Sensitivity and Fuzzy Set Theory (DEA) as well as Bayesian Analysis and Heterogeneity (SFA) are found to be most influential research areas and seem to be methodological trends. By developing an adoption rate of knowledge we identify that research, in terms of citations, is more focusing on relatively old and recent research at the expenses of middle-aged contributions, which is a typical phenomenon of a fast developing discipline.     

统计分析方法在市场调研前期的应用

本文基于聚类分析和判别分析 ,对在众多的区域市场中如何选取一个或几个有代表性的区域市场进行了一些探索性的研究。并利用这种方法进行了一个关于在新产品上市的营销策划中如何进行营销试点市场的选取的实证分析     

数学建模在多元统计分析教学中的应用

本利用数学建模的思想对多元统计分析特别是主成分分析方法的教学进行改革，通过使用统计软件SPSS进行计算和分析，使学生对十分抽象的统计概念和深奥的多元统计理论有直现的认识和理解，为掌握多元统计分析方法提供了较好的手段。     

Ratio-based RTS determination in weight-restricted DEA models

This paper provides computationally efficient approaches for determining to which returns to scale (RTS) class a unit belongs in weight-restricted Data Envelopment Analysis (DEA) models. A non-traditional computational algorithm is introduced. The suggested approach is based on the calculation of certain ratios within the data set and offers obvious computational advantages over the traditional approaches involving the solution of standard DEA models. Some theorems and algorithms are given. Computational advantages of the provided results are discussed and one of the algorithms is illustrated using real world data.     

Scaling units via the canonical correlation analysis in the DEA context

This paper deals with the evaluation of decision making units which have multiple inputs and outputs. A new method (CCA/DEA) is developed where the Canonical Correlation Analysis (CCA) is utilized to provide a full rank scaling for all the units rather than a categorical classification (for efficient and inefficient units) as done by the Data Envelopment Analysis (DEA). The CCA/DEA approach is an attempt to bridge the gap between the frontier approach of DEA and the average tendencies of statistics (econometrics). Nonparametric statistical tests are employed to validate the consistency between the classification from the DEA and the postclassification that was generated by the CCA/DEA.     

Idempotent Functional Analysis: An Algebraic Approach

This paper is devoted to Idempotent Functional Analysis, which is an abstract version of Idempotent Analysis developed by V. P. Maslov and his collaborators. We give a brief survey of the basic ideas of Idempotent Analysis. The correspondence between concepts and theorems of traditional Functional Analysis and its idempotent version is discussed in the spirit of N. Bohr's correspondence principle in quantum theory. We present an algebraic approach to Idempotent Functional Analysis. Basic notions and results are formulated in algebraic terms; the essential point is that the operation of idempotent addition can be defined for arbitrary infinite sets of summands. We study idempotent analogs of the basic principles of linear functional analysis and results on the general form of a linear functional and scalar products in idempotent spaces.     

Convex approximations to sparse PCA via Lagrangian duality

We derive a convex relaxation for cardinality constrained Principal Component Analysis (PCA) by using a simple representation of the L₁ unit ball and standard Lagrangian duality. The resulting convex dual bound is an unconstrained minimization of the sum of two nonsmooth convex functions. Applying a partial smoothing technique reduces the objective to the sum of a smooth and nonsmooth convex function for which an efficient first order algorithm can be applied. Numerical experiments demonstrate its potential.     

Finding strong defining hyperplanes of Production Possibility Set

Production Possibility Set (PPS) is defined as the set of all inputs and outputs of a system in which inputs can produce outputs. Data Envelopment Analysis models implicitly use PPS to evaluate relative efficiency of Decision Making Units (DMUs). Although DEA models can determine the efficiency of a DMU, they cannot present efficient frontiers of PPS. In this paper, we propose a method for finding all Strong Defining Hyperplanes of PPS (SDHP). They are equations that form efficient surfaces. These equations are useful in Sensitivity and Stability Analysis, the status of Returns to Scale of a DMU, incorporating performance information into the efficient frontier analysis and so on.     

我国城市设施水平的主成分分析

本文提出多元统计分析的一种评价方法：通过对全国31个省市自治区的城市设施水平进行主成分分析，就各地区城市设施水平进行统计评价，揭示我国城市的发展质量、城市居民的生活质量，找出各地区在设施建设各方面的优势与不足，为我国今后的城市化道路提供科学的参考依据。