选择价值工程改进对象的动态排序模型

从一个复杂系统中,合理地选择重点改进对象,是有效开展价值工程活动的基础。本文在分析最合适区域法存在的问题的基础上,提出选择价值工程改进对象的动态排序模型。     

《世界经济地理》教材编写体系研究

本文从理论上探讨世界经济地理研究的依据和体系,指出现行教材编写存在的问题,提出编写的新建议。认为世界经济地理侧重研究经济区→经济地域→经济地域系统及其运动规律,认为存在世界和国家级区域级别差异。为此,本文认为教材编写时要强调条件要素要与经济地域和经济地域系统形成发展过程一起进行论述,要突出研究对象的等级层次关系,突出城市或城市群的地位与作用,并要加强国家经济国际化进程对经济地域形成发展的影响作用。     

知识经济与广州城市性质功能定位

本文认为,面对２１ 世纪和知识经济时代,广州城市性质与功能的定位必然产生变化。广州要发展,必须发展知识经济,确立由４ 个系统组成的广州知识经济创新体系,确立教育和科技产业成为知识经济产业的一个支柱部门,成为广州发展的主导因素之一。为此,广州城市性质与功能应该定位为华南地区、东南亚地区的教育科技城和以知识经济产业为主体的多功能的中心城市     

论动物转基因科研试验安全监管的法律制度

动物转基因技术种类日益复杂,应用范围不断扩大,但成本和技术要求却不断降低,生物风险和安全威胁越来越大。科研试验阶段是风险防控的关键,因此需要科学而严谨的科研试验法律监管,以预防意外和不正当试验对社会及生态造成不良影响。国内可以指向转基因动物科研试验监管适用的法律规定集中于农业应用领域,不足以形成全面有效的监管。基于动物转基因技术的发展现状和趋势,需要对现有法律法规进行分析,明确科研试验监管的基本原则,以协调监管体系为核心探讨法律完善的关键问题,进而系统性地明确科研试验安全监管法律的进展趋势。     

试论时间价值观

时间是一种重要的资源。时间价值观是个体以自身的需要为尺度对时间重要性的稳定态度和观念。时间价值观含有时间资源观、时间效率观、时机观、时间顺序观等方面的意义。时间价值观的结构可以有不同的划分。时间价值观受社会文化传统、个体的年龄因素、个体性格、社会环境等因素的影响。心理学对时间价值观的研究在理论上和应用中都有着重要的意义     

教育对经济增长影响的实证分析——以陕西省为例

运用菲德模型,以陕西省为例,测定教育部门对经济增长的全部作用和教育对经济中其他部门的外溢作用。结果表明,陕西省教育部门的边际生产力高于经济部门的边际生产力,但仍是相当的低。陕西省教育目前主要是通过外溢作用间接对经济发展发挥作用,其直接作用远远没有发挥出来,甚至表现为负的作用,教育部门的效率有待发挥。基于此,提出加大教育投入力度,深化教育部门内部改革,加快建设市场经济体制以充分发挥教育对经济的促进作用。     

Modelling small and medium enterprise loan defaults as rare events: the generalized extreme value regression model

A pivotal characteristic of credit defaults that is ignored by most credit scoring models is the rarity of the event. The most widely used model to estimate the probability of default is the logistic regression model. Since the dependent variable represents a rare event, the logistic regression model shows relevant drawbacks, for example, underestimation of the default probability, which could be very risky for banks. In order to overcome these drawbacks, we propose the generalized extreme value regression model. In particular, in a generalized linear model (GLM) with the binary-dependent variable we suggest the quantile function of the GEV distribution as link function, so our attention is focused on the tail of the response curve for values close to one. The estimation procedure used is the maximum-likelihood method. This model accommodates skewness and it presents a generalisation of GLMs with complementary log–log link function. We analyse its performance by simulation studies. Finally, we apply the proposed model to empirical data on Italian small and medium enterprises.     

The economic design of multivariate binomial EWMA VSSI control charts

Since multi-attribute control charts have received little attention compared with multivariate variable control charts, this research is concerned with developing a new methodology to employ the multivariate exponentially weighted moving average (MEWMA) charts for m-attribute binomial processes; the attributes being the number of nonconforming items. Moreover, since the variable sample size and sampling interval (VSSI) MEWMA charts detect small process mean shifts faster than the traditional MEWMA, an economic design of the VSSI MEWMA chart is proposed to obtain the optimum design parameters of the chart. The sample size, the sampling interval, and the warning/action limit coefficients are obtained using a genetic algorithm such that the expected total cost per hour is minimized. At the end, a sensitivity analysis has been carried out to investigate the effects of the cost and the model parameters on the solution of the economic design of the VSSI MEWMA chart.     

Extended generalised Pareto models for tail estimation

The most popular approach in extreme value statistics is the modelling of threshold exceedances using the asymptotically motivated generalised Pareto distribution. This approach involves the selection of a high threshold above which the model fits the data well. Sometimes, few observations of a measurement process might be recorded in applications and so selecting a high quantile of the sample as the threshold leads to almost no exceedances. In this paper we propose extensions of the generalised Pareto distribution that incorporate an additional shape parameter while keeping the tail behaviour unaffected. The inclusion of this parameter offers additional structure for the main body of the distribution, improves the stability of the modified scale, tail index and return level estimates to threshold choice and allows a lower threshold to be selected. We illustrate the benefits of the proposed models with a simulation study and two case studies.     

Changepoint Estimation in a Segmented Linear Regression via Empirical Likelihood

For a segmented regression system with an unknown changepoint over two domains of a predictor, a new empirical likelihood ratio statistic is proposed to test the null hypothesis of no change. Under the null hypothesis of no change, the proposed test statistic is shown empirically to be Gumbel distributed with robust location and scale estimators against various parameter settings and error distributions. A power analysis is conducted to illustrate the performance of the test. Under the alternative hypothesis with a changepoint, the test statistic is utilized to estimate the changepoint between the two domains. A comparison of the frequency distributions between the proposed estimator and two parametric methods indicates that the proposed method is effective in capturing the true changepoint.