原油价格变动对中国基础工业收益的影响——基于格兰杰因果关系检验的实证研究

以2006年1月4日-2014年7月31日的日数据为样本,采用向量自回归模型(VAR模型)、非线性检验、线性格兰杰因果关系检验、非线性格兰杰因果关系检验,选取电力及公用事业、钢铁、机械、基础化工、煤炭、原油石化六大基础工业,从行业角度研究原油价格对中国经济的影响关系。实证结果表明:原油价格变化率与钢铁、煤炭、石油石化行业存在显著的双向线性格兰杰因果关系,机械、基础化工到原油价格变化率存在显著的单向线性格兰杰因果关系,电力及公共事业与原油价格不存在线性格兰杰因果关系;原油价格变化率与6个基础工业存在显著地双向非线性因果关系。     

基于低碳经济视角的建设公共工程项目的前提条件评价

将低碳经济发展的要求与公共工程项目建设的前提条件相结合,采用修正的QFD技术这一评价模型,提出一个普适性的、可以有效监督评测建设这类项目的前提需求的评价指标体系。研究表明该评价体系为开展公共工程项目建设前提条件评价提供了参考依据,能够较好地体现低碳经济的需求,使基于低碳经济需求下公共工程项目的建设有针对性,更加科学有效。     

立式盘类转子动平衡机箱体有限元分析

旋转电极式电除尘器出口粉尘体积分数小,可降低PM2.5排放量,是目前新建和改造电除尘器的主流方向之 一,其清灰刷关系到旋转电极式电除尘器的除尘效率和使用寿命,为此搭建了清灰刷失效形式和寿命测试试验装置,其 中机械部分为框架结构,电气部分采用PLC控制,由减速变频电机驱动,最后通过ANSYS Workbench对其主要部件进行 了静态和动态性能分析,结果表明：装置框架的动态特性满足设计要求,不会在工作时引起共振,运行后该装置能够满足 试验工作需要。     

秩估计及向量广义线性模型在风险投资中应用

从风险投资案例中整理发现内在变化规律,有助于把握投资方向和路径。以2001—2011年全球投资公司每轮平均投资数据为例,由于数据不具备正态性和方差齐次性,基于秩估计方差分析,结果表明,各年之间均值存在显著差异。假设平均投资服从伽玛分布,其形状参数和尺度参数是年份的二次函数,基于向量广义线性模型估计各参数。最后预测2015年伽玛分布形状参数为1．1959,尺度参数为5816．186。风险投资位于任何区间的概率都可以通过分布函数计算。     

“英语语言表达能力”概念界定及评价指标研究

语言是交流的工具,交流包含“听”“读”语言理解和“说”“写”语言表达两个过程,语言表达是实现交流的核心所在.培养学生英语表达技能是英语教学的重要目标.然而如何评价英语语言表达能力？评价的指标是什么？对此,英语教学实践中的操作标准不太统一和明确.文章以“说”和“写”的教学要求和测试评价标准为视点,采用关键词分析法对现行的国内外两个外语教学纲领性文件和三个权威英语测试评分标准进行了对比分析,概括出对语言表达能力共同的要求.文章还从心理学和认知语言学的学科视角,界定了英语语言表达能力的概念,分析了其组成要素,提出了三维评价指标,并解释了英语语言表达能力组成要素和指标间的相互关系,强调了思维在英语语言表达能力中的重要性.     

A New Test for Short Memory in Long Memory Time Series

This article considers short memory characteristics in a long memory process. We derive new asymptotic results for the sample autocorrelation difference ratios. We used these results to develop a new portmanteau test that determines if short memory parameters are statistically significant. In simulations, the new test can detect short memory components more often than the Ljung-Box test when these short memory components are in fact within a long memory process. Interestingly, our test finds short memory autocorrelations in U.S. inflation rate data, whereas the Ljung-Box test fails to find these autocorrelations. Modeling these short memory autocorrelations of the inflation rate data leads to improved model accuracy and more precise prediction.     

A randomized Baumgartner statistic for multivariate two-sample testing hypothesis

In this paper, multivariate two-sample testing problems were examined based on the Jure?ková–Kalina's ranks of distances. The multivariate two-sample rank test based on the modified Baumgartner statistic for the two-sided alternative was proposed. The proposed statistic was a randomized statistic. Simulations were used to investigate the power of the suggested statistic for various population distributions.     

A survey on multivariate chi-square distributions and their applications in testing multiple hypotheses

We are concerned with three different types of multivariate chi-square distributions. Their members play important roles as limiting distributions of vectors of test statistics in several applications of multiple hypotheses testing. We explain these applications and consider the computation of multiplicity-adjusted p-values under the respective global hypothesis. By means of numerical examples, we demonstrate how much gain in level exhaustion or, equivalently, power can be achieved with corresponding multivariate multiple tests compared with approaches which are only based on univariate marginal distributions and do not take the dependence structure among the test statistics into account. As a further contribution of independent value, we provide an overview of essentially all analytic formulas for computing multivariate chi-square probabilities of the considered types which are available up to present. These formulas were scattered in the previous literature and are presented here in a unified manner.     

Stationary bootstrapping for panel cointegration tests under cross-sectional dependence

Stationary bootstrapping is applied to panel cointegration tests which are based on the ordinary least-squares estimator and the seemingly unrelated regression (SUR) estimator of the residual unit root. Large sample validity of stationary bootstrapping is established. A finite sample experiment reveals that size performances of the bootstrap tests are much less sensitive to cross-sectional correlation than those of existing tests and a test based on the SUR estimator has substantially better power than existing tests.