变系数联立模型的局部线性广义矩变窗宽估计

在随机设计条件下,提出了一类变系数联立模型,运用局部线性广义矩变窗宽估计,对模型的变系数进行了估计,研究了估计量的大样本性质.利用概率论中大数定律和中心极限定理,证明了估计量的大样本性质,局部线性广义矩变窗宽估计具有相合性和渐进正态性.     

Supporting hydrogen based transportation: case studies with Global MARKAL Model

Steadily growing prices of oil and emissions coming from conventional vehicles, might force a switch to an alternative and less polluting fuel in the coming future. In this article we analyze the potential influence of selected factors for successful market penetration of hydrogen fuel cell vehicles in hydrogen based private transportation economy. Using a world scale, full energy system, bottom-up, optimization model (Global MARKAL Model—GMM) we address the possibility of supporting the fuel cell vehicle technology to become competitive in the markets. In a series of optimizations we evaluate the potential influence of governmental supports and the internalization of externalities related to CO₂ and local pollution emissions originating from the transportation sector, as well as preferential crediting options and demonstration projects promoting fuel cell vehicles. The results suggest that the crucial element is the price of fuel cells and their further potential to reduce costs. This reduction of costs may be triggered by governmental support such as direct subsidies to fuel cells, preferential crediting options for the buildup of hydrogen infrastructure as well as penalization of emitters of CO₂ and/or local pollutants.     

Abnormal crowd behavior detection by using the particle entropy

The crowd distribution information is the crucial information for abnormal behaviors detection in the crowd scenes. In this paper, we firstly refer to the definition of the entropy and propose an algorithm effectively and accurately representing the crowd distribution information in the crowd scenes. The proposed algorithm not only avoids unstable foreground extraction, but also owns low computational complexity. To detect the abnormal crowd behaviors, we use the Gaussian Mixture Model (GMM) over the normal crowd behaviors to predict the abnormal crowd behaviors since GMM usually can deal well with the unbalanced problem. In this paper we simultaneously use the crowd distribution information and the crowd speed information to estimate the parameters of GMM over the normal crowd behaviors and predict abnormal crowd behaviors. Experiment conducted on publicly available dataset consisting of gathering and dispersion events validates that the proposed approach can preeminently reflect the crowd distribution information. In addition, experiments conducted on publicly UMN dataset demonstrate that the proposed abnormal crowd behavior detection method has an excellent performance and outperforms the state-of-the-art methods.     

Thermal analysis as a tool in the study of GMM in Angra Dos Reis region,Rio de Janeiro,Brazil

Angra dos Reis/Itaguai region of the state of Rio de Janeiro, Brazil, is a very problematic area due to the instability of slope and landslides, due to geological and geomorphological conditions and to the significant and continuous human occupation over favorable areas is prone to the triggering of landslides. The samples were analyzed by thermogravimetry (TG), derivative thermogravimetry (DTG) and differential thermal analysis (DTA). This paper analyzes and characterizes the clay minerals and presence of water, gravitational mass movements’ sites and compares it with sites where gravitational mass movements do not occur. Indeed, this analysis also attempts to verify the presence of minerals.     

对CAPM模型检验中独立同分布正态假设重要性的实证分析

金融市场的数据大多不是iid正态的,但是通常针对CAPM的Wald检验和F检验均是基于这一假设的。本文采用一种不需要iid正态假定的基于GMM方法的检验统计量,对同一原假设进行了检验,并且将结果与美国和澳大利亚股市的实证结果进行了比较。结果表明上海股市的确不满足iid正态,而且GMM统计量的检验结果和通常的检验存在差异并有可能影响到判别的结果。     

动态变系数回归模型的识别与非参数GMM估计

主要研究关于面板数据的有限阶固定效应的动态变系数回归模型(简称FDVCM)的统计推断问题.基于B-样条函数和广义矩估计(简称GMM)方法,首先建立了未知系数函数的非参数GMM估计,并证明大样本情形下该估计达到最优非参数收敛速度且具有渐近正态性质.然而实际问题中模型的动态阶数完全未知,也可能存在其它冗余的回归变量,文中借助文[Fan J,Li R.Variable selection via penalized likelihood and its oracle properties.Journal of the American Statistical Association,2001,96(456):1348-1360]中的smoothly clipped absolute deviation(简称SCAD)惩罚函数同时识别真实的动态阶数和显著的外生回归变量.同时建立了压缩估计的Oracle性质,即所识别的模型与真实模型中的参数估计具有相同的渐近分布.最后,无论是数值试验还是实例数据分析都验证了本文方法的合理性和可行性.     

现金持有动态调整机制——基于动态面板模型的实证分析

本文通过建立动态面板数据模型,系统地研究了中国企业现金持有的动态调整机制。发现:第一,企业存在最优目标现金持有水平,现金持有策略倾向于围绕这一目标进行动态调整,但是我国资本市场动态调整的成本较高;第二,现金持有不足企业的调整速度快于超额现金持有企业的调整速度,这说明,相对于超额现金持有带来的代理成本负面影响,企业更加倾向于关注现金持有不足所产生的流动性短缺风险。并且统计过程表明系统广义矩方法在动态面板模型估计中具有合理性。     

面板数据空间误差分量模型的GMM估计及其应用

本文研究面板数据空间误差分量模型(Spatial Error Components Model,SEC)的估计方法。为克服极大似然法在SEC模型估计中运算的困难,本文提出基于广义矩估计的可行广义最小二乘法(GMM-GLS),证明了估计量的一致性及有限样本下的有效性;并应用此模型,研究2000-2007年中国30个省(西藏除外)的物质资本存量、人力资本存量及能源消耗对实际GDP的影响,结果表明,采用SEC模型所得估计结果更为符合经济现实。     

人民币汇率变动对我国对外投资的影响研究

通过GARCH模型和动态面板模型,对人民币汇率变动对我国对外直接投资的影响进行了实证分析.结果表明:在长期内,人民币汇率无论是汇率水平变化还是汇率波动都对我国对外直接投资存在影响,人民币升值,我国对外直接投资增加;汇率波动幅度越大,我国对外直接投资也会增加.