企业经济效益的综合分析与评价：因子分析法的应用

企业经济效益评价往往涉及众多指标,利用多指标评价企业经济效益,使评价问题变得复杂,本采用多元统计中的因子分析法来解决这一问题,介绍了分析、评价过程。     

聚类分析在经济指标分类选择中的应用

经济效益是一个极为重要的问题,使用什么样的经济效益指标来评价企业经济效益,至今没有统一定论;没有明确的一套指标,就不能准确地反映企业经济效益的状况.本文就多元统计理论中的聚类分析对经济效益指标进行分类,在分“类”确定后,就可以从每“类”中,根据经济统计理论造出若干“代表”。组成一套反映企业经济效益的指标.为确定一套考核评价企业经济效益的指标作一尝试. 对指标进行聚类分析是根据指标之间的关系来进行的,本文采用指标之间的相关系数作     

企业经济效益的主成分分析

经济效益是经济工作的中心，提高经济效益是企业经营管理的基本要求。本运用主成分分析法，把评价企业经济效益的多指标转化为少数几个综合指标，抓住复杂经济问题的主要矛盾，为经营、投资提供有价值的参考，为宏观调控和企业的科学管理提供了简明、规范的评价方法。     

企业经济效益综合评价方法探讨

企业经济效益综合评价方法探讨吴锡林，王树筠（南开大学分校）（天津大学分校）经济效益评价是经济管理的重要内容之一，工业企业的生产经营活动是一个互相制约、彼此关联的有机整体。因此，企业经济效益的评价一般地表现为多指标的综合评价问题。它是从需要出发，以多个...     

多元统计分析在综合评判企业经济效益中的应用

经济效益的考核与评价是企业经济活动分析的重要课题.目前,我国考核企业经济效益的主要指标有:固定资产利税率、销售收入利税率、资金利税率、全员劳动生产率等等.这套指标体系比较全面地反映了企业经济效益各个侧面的状况,但在实际考核企业经济效益时往往莫衷一是.因为指标之间彼此常出现此大彼小,此低彼高的现象,各指标间又有着相互的联系,这就使得评价比较诸企业经济效益有一定困难.本文应用多元统计分析中的因子分析方法,绘出全国重点水泥厂经济效益综合评价与分析,并用聚类分析方法根据企业经济效益的主要指标把企业划分等级. 一、因子…     

对企业经济效益综合指标数学模型的研究

我们知道,在企业经营管理中,一般是通过多项技术经济指标反映企业生产经营的好坏,而要根据多项指标对企业的经济效益作出综合评价并非易事.这是因为从理论上看这些指标是相互联系的,而在现实的经济领域中,它们的完成情况又常常是各有长短,参差不齐.如何利用现行的经济效益指标来全面评价企业生产经营水平和经济效果优劣,这是经济学界长期研究和探索的问题,也是企业管理中急需解决的问题. 《数理统计与管理》1986年第3期刊登了高元源、毕凤英两同志的文章:《用二级判别法评价企业综合经济效益的探讨》(以下简称高文)1987年第4期又刊登了孙书…     

关于企业综合经济效益评价模型的讨论──兼与孙书安、刘贤龙等同志商榷

对工业企业活动的经济效益进行定量的计算和比较,是工业管理中的重要课题.利用现有的反映企业经济效益的指标体系,构造客观、合理的综合经济效益评价模型是这个课题的重要之一. 《数理统计与管理》分别于1986年第3期刊登了高元源、毕凤英二同志的《用二级判别法评价企业综合经济效益的探讨》(以下称高文)、1987年第4期刊登了刘贤龙的《对企业经济效益综合指标数学模型的研究》(以下称刘文)三篇文章,对如何正确应用多元统计分析的理论和方法建立企业综合经济效益的评价模型进行了有益的探讨.笔者就上述几文存在的问题陈一管见,并与诸作者的商…     

改革以来我国宏观经济效益的综合评价

科学评价经济效益是一个具有重要意义的问题。目前,反映宏观经济效益的指标有数十种之多,用任何单一指标都无法对经济效益作出较为全面确切的评价。若选取一些重要指标构造一个单一综合指标,在指标对口径、权重选择、经济效益含义方面都很难统一。因此,越来越多的专家、学者倾向于设计一套指标体系来系统反映宏观经济效益,在此基础上,采用某种多指标综合评价方法进行综合评价。本文将试图选择9个有代表性的指标作为宏观经济效益的指标体系,系统反映改革以来我国宏观经济效益的变化情况,并运用极值无量纲化方法、多目标决策中的目标规划法和…     

用多元分析方法评价企业经济效益的初探

目前我国对企业经济效益的评价与改核常常只用一两个效益指标(如固定资产净值、利税总额),这种方法不能全面反映企业的经营情况。本文用主成分分析和因子分析法,结合实例作出全面评价企业经济效益的尝试,同时利用逐步聚类分析法根据企业的主要效益指标给出企业的等级划分办法。一样本数据的收集说明我们在贵州省大中型企业中选取了20个企业作为样本,主要的经济效益指标是:x_1为平均每一职工创造工业净产值(元);x_2为平均每一职工实现产品销售收入(元);x_3为百元物耗     

加权主成份分析在多指标综合评价中的运用

经济效益的综合评价一般表现为多指标综合评价的问题,即我们需要根据多个从不同方面反映经济效益的指标综合评价经济效益。厉无畏[1]提出用主成份分析求出一个综合性指标代替多项经济效益指标,然后据此综合性指标进行评价。由于这种方法尽可能地利用了原来多项指标中的信息,所以不失为一种可取的方法。 但是,由主成份分析求得的综合指标,是从原指标的变异程度和相互关系出发,不反映现实中原指标重要程度上的差异。这是因为主成份分析是基于原指标的协方差矩阵来求综合指标的,而对原指标中哪些指标经济意义较大、在实际中举足轻重,哪些指标经…     

对台湾工农业产品产量的主成分分析

主成分析分析法是一种将多个指标化为少数几个不相关的综合指标 (即主成分 )的多元统计分析方法 .本文通过运用主成分方法对我国台湾地区 1 989 1 996工农业主要指标的原始数据的处理分析 ,表明主成分分析确是在实用中很可行的一种常用的统计方法 .     

Efficiency and benchmarking with directional distances: a data-driven approach

In efficiency analysis the assessment of the performance of Decision-Making Units (DMUs) relays on the selection of the direction along which the distance from the efficient frontier is measured. Directional Distance Functions (DDFs) represent a flexible way to gauge the inefficiency of DMUs. Permitting the selection of a direction towards the efficient frontier is often useful in empirical applications. As a matter of fact, many papers in the literature have proposed specific DDFs suitable for different contexts of application. Nevertheless, the selection of a direction implies the choice of an efficiency target which is imposed to all the analysed DMUs. Moreover, there exist many situations in which there is no a priori economic or managerial rationale to impose a subjective efficiency target. In this paper we propose a data-driven approach to find out an ‘objective’ direction along which to gauge the inefficiency of each DMU. Our approach permits to take into account for the heterogeneity of DMUs and their diverse contexts that may influence their input and/or output mixes. Our method is also a data-driven technique for benchmarking each DMU. We describe how to implement our framework and illustrate its usefulness with simulated and real data sets.     

Review of ranking methods in the data envelopment analysis context

Within data envelopment analysis (DEA) is a sub-group of papers in which many researchers have sought to improve the differential capabilities of DEA and to fully rank both efficient, as well as inefficient, decision-making units. The ranking methods have been divided in this paper into six, somewhat overlapping, areas. The first area involves the evaluation of a cross-efficiency matrix, in which the units are self and peer evaluated. The second idea, generally known as the super-efficiency method, ranks through the exclusion of the unit being scored from the dual linear program and an analysis of the change in the Pareto Frontier. The third grouping is based on benchmarking, in which a unit is highly ranked if it is chosen as a useful target for many other units. The fourth group utilizes multivariate statistical techniques, which are generally applied after the DEA dichotomic classification. The fifth research area ranks inefficient units through proportional measures of inefficiency. The last approach requires the collection of additional, preferential information from relevant decision-makers and combines multiple-criteria decision methodologies with the DEA approach. However, whilst each technique is useful in a specialist area, no one methodology can be prescribed here as the complete solution to the question of ranking.     

The pebbling threshold of the square of cliques

Given an initial configuration of pebbles on a graph, one can move pebbles in pairs along edges, at the cost of one of the pebbles moved, with the objective of reaching a specified target vertex. The pebbling number of a graph is the minimum number of pebbles so that every configuration of that many pebbles can reach any chosen target. The pebbling threshold of a sequence of graphs is roughly the number of pebbles so that almost every (resp. almost no) configuration of asymptotically more (resp. fewer) pebbles can reach any chosen target. In this paper we find the pebbling threshold of the sequence of squares of cliques, improving upon an earlier result of Boyle and verifying an important instance of a probabilistic version of Graham's product conjecture.     

False targets efficiency in defense strategy

The paper analyzes the efficiency of deploying false targets as part of a defense strategy. It is assumed that the defender has a single object that can be destroyed by the attacker. The defender distributes its resource between deploying false targets and protecting the object from outside attacks. The attacker cannot distinguish the false targets from the defended object (genuine target). Therefore the attacker has no preferences for attacking one target rather than another target. The defender decides how many false targets to deploy whereas the attacker decides how many targets to attack. The article assumes that both the defender and attacker have complete information and full rationality. The optimal number of false targets and the attacked targets are obtained for the case of fixed and variable resources of the defender and the attacker as solutions of a non-cooperative game between the two agents.     

需多发命中时毁伤时间的分布与特征

本研究带有搜索系统并且毁伤目标需要多发命中的格斗模型,并利用更新方程导出了毁伤目标所需时间的分布密度与特征函数。最后,章用实例说明了计算过程。     

Dynamically Rescaled Hamiltonian Monte Carlo for Bayesian Hierarchical Models

Dynamically rescaled Hamiltonian Monte Carlo is introduced as a computationally fast and easily implemented method for performing full Bayesian analysis in hierarchical statistical models. The method relies on introducing a modified parameterization so that the reparameterized target distribution has close to constant scaling properties, and thus is easily sampled using standard (Euclidian metric) Hamiltonian Monte Carlo. Provided that the parameterizations of the conditional distributions specifying the hierarchical model are “constant information parameterizations” (CIPs), the relation between the modified- and original parameterization is bijective, explicitly computed, and admit exploitation of sparsity in the numerical linear algebra involved. CIPs for a large catalogue of statistical models are presented, and from the catalogue, it is clear that many CIPs are currently routinely used in statistical computing. A relation between the proposed methodology and a class of explicitly integrated Riemann manifold Hamiltonian Monte Carlo methods is discussed. The methodology is illustrated on several example models, including a model for inflation rates with multiple levels of nonlinearly dependent latent variables. Supplementary materials for this article are available online.     

On characterizing full dimensional weak facets in DEA with variable returns to scale technology

The frontier of the Production Possibility Set (PPS) consists of two types of full dimensional facets, efficient and weak facets. Identification of all facets of the PPS can be used in sensitivity and stability analysis, to find the closet target for inefficient Decision-Making Units (DMUs), and to determine the status of returns to scale of a DMU, among others. There has been a surge of articles on determining efficient facets in recent years. There are, however, many cases where knowledge of weak facets is required for a thorough analysis. This is the case, in particular, when the frontier of the PPS is constructed only of weak facets. The existing algorithms for finding weak facets either require knowledge of all extreme directions of the PPS or applicable only under some restrictions on the position of weak efficient DMUs. We provide a complete characterization of weak facets. Using this characterization, we then devise a different algorithm to find weak facets. We illustrate our algorithm using a numerical example.     

On the minimality of search paths under absolutely continuous univariate distributions

The linear search problem is concerned with the search for a target located randomly on a line. The target being sought for might be on either side of some starting point. A searcher makes for the target with an upper bound on his speed, using a continuous search path in which he changes his direction many times before reaching his goal. The minimality of average distance (time) from the starting point upon reaching the target is the measure of optimality of search paths. We have obtained sufficient conditions that guarantee the minimality of such search paths whenever the target has an absolutely continuous distribution.

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Zusammenfassung Ein Objekt, das sich in zufälliger Position auf einer Strecke befindet, soll gesucht werden; der Startpunkt liegt im Inneren der Strecke. Für die Bewegungsgeschwindigkeit bei der Suche ist eine obere Schranke gegeben; der Suchpfad muß stetig sein, wobei beliebig viele Richtungsänderungen zugelassen sind. Das Ziel ist die Minimierung der erwarteten Zeit bis zum Erreichen des Objekts. Unter der Voraussetzung einer absolut stetigen Verteilung für die Position des Objekts werden hinreichende Bedingungen für die Optimalität eines Suchpfades angegeben.

     

基于Probit模型的学生补考率影响因素分析

近年来,高校教务管理中出现了学生补考率过高的病态现象.通过引入诸多可能影响学生学习成绩的因素,分析了内蒙古工业大学信息与计算科学专业学生出现补考现象的原因.通过问卷调查获得相关数据,利用二元Probit模型分析影响学生补考概率的主要因素,从数量上研究各个影响因素对补考概率的作用方向及其程度.得到的结果表明:课程教师受学生欢迎程度、课外学习时间的多少、对所学专业的了解程度、毕业后择业目标等因素都在一定的程度上影响其补考率.通过定量和定性分析,对如何减少学生补考率,提高教学质量提出了一些有价值的建议.