A classifier for multi-dimensional datasets based on Bayesian multiple kernel grouping learning

This paper proposes an algorithm for the classification of multi-dimensional datasets based on the conjugate Bayesian Multiple Kernel Grouping Learning (BMKGL). Using conjugate Bayesian framework improves the computation efficiency. Multiple kernels instead of a single kernel avoid the kernel selection problem which is also a computationally expensive work. Through grouping parameter learning, BMKGL can simultaneously integrate information from different dimensions and find the dimensions which contribute more to the variations of the outcome for the purpose of interpretable property. Meanwhile, BMKGL can select the most suitable combination of kernels for different dimensions so as to extract the most appropriate measure for each dimension and improve the accuracy of classification results. The simulation results illustrate that our learning process has better performance in prediction results and stability compared to some popular classifiers, such as k-nearest neighbours algorithm, support vector machine algorithm and naive Bayes classifier. BMKGL also outperforms previous methods in terms of accuracy and interpretation for the heart disease and EEG datasets.     

宏观测度的边界悖律及其意义

 本文论述了本体论意义、认识论意义和边界操作意义上的宏观测度边界,提出了宏观测度边界悖律的理论命题,分析了形成测度边界悖律的深层次原因和宏观测度越界的可能后果,强调了明确宏观测度边界悖律的意义,探讨了核算范式转换问题和替代测度的有效性问题。     

On the bias and mean square error of the least square estimator in a regression model with two inequality constraints and multivariate t error terms

We derive and numerically evaluate the bias and mean square error of the inequality constrained least squares estimator in a model with two inequality constraints and multivariate terror terms. Our results suggest that qualitatively, the estimator properties found for models with normal errors carry over to the case of multivariate terrors.     

Modeling Dependence in High Dimensions With Factor Copulas

This article presents flexible new models for the dependence structure, or copula, of economic variables based on a latent factor structure. The proposed models are particularly attractive for relatively high-dimensional applications, involving 50 or more variables, and can be combined with semiparametric marginal distributions to obtain flexible multivariate distributions. Factor copulas generally lack a closed-form density, but we obtain analytical results for the implied tail dependence using extreme value theory, and we verify that simulation-based estimation using rank statistics is reliable even in high dimensions. We consider “scree” plots to aid the choice of the number of factors in the model. The model is applied to daily returns on all 100 constituents of the S&P 100 index, and we find significant evidence of tail dependence, heterogeneous dependence, and asymmetric dependence, with dependence being stronger in crashes than in booms. We also show that factor copula models provide superior estimates of some measures of systemic risk. Supplementary materials for this article are available online.     

Spatial prediction of crystalline defects observed in molecular dynamic simulations of plastic damage

Molecular dynamic computer simulation is an essential tool in materials science to study atomic properties of materials in extreme environments and guide development of new materials. We propose a statistical analysis to emulate simulation output with the ultimate goal of efficiently approximating the computationally intensive simulation. We compare several spatial regression approaches including conditional autoregression (CAR), discrete wavelets transform (DWT), and principle components analysis (PCA). The methods are applied to simulation of copper atoms with twin wall and dislocation loop defects, under varying tilt tension angles. We find that CAR and DWT yield accurate results but fail to capture extreme defects, yet PCA better captures defect structure.     

西部开发的先声：抗战时期西部农业科技之推广

战时西部地区农业科学技术推广,既是抗战史境下的一项经济政策,也是西部大开发之先声。该措施不仅有效地支持了中国的抗战事业,且对于促进西部农业的发展,加速其现代化进程,发挥了重要作用。     

公司治理强度、审计力度与审计质量

自安然事件以来,公司治理和外部审计的重要性得到了前所未有的重视.本文构建了一个公司所有者与外部审计师之间的博弈理论模型,以分析均衡状态下公司治理强度、审计力度与审计质量之间的关系,并讨论所有者和审计师赔偿责任对博弈均衡的影响.我们特别引入了公司治理成本函数和审计成本函数,并同时考虑了公司所有者和审计师的赔偿责任.在本模型中,公司所有者对公司治理强度的决策和外部审计师对审计力度的决策共同影响审计报告对外部投资者的信息有用性(即审计质量),并最终影响了公司的成交价格.研究得到的主要结论是:(1)均衡状态下公司治理强度的增加有助于提升审计力度和审计质量;(2)所有者赔偿责任的增加只会提高公司成交价格,但不会影响博弈均衡和均衡状态下的审计质量;(3)审计师赔偿责任的增加并不一定导致所有者降低公司治理强度,且只有在特定情况下才能提升审计力度和审计质量.     

The closed-loop supply chain network with competition,distribution channel investment,and uncertainties

In this paper, a closed-loop supply chain network is investigated with decentralized decision-makers consisting of raw material suppliers, retail outlets, and the manufacturers that collect the recycled product directly from the demand market. We derive the optimality conditions of the various decision-makers, and establish that the governing equilibrium conditions can be formulated as a finite-dimensional variational inequality problem. We establish convergence of the proposed algorithm that can allow for the discussion of the effects of competition, distribution channel investment, yield and conversion rates, combined with uncertainties in demand, on equilibrium quantity transactions and prices. Numerical examples are provided for illustration.     

Emerging Market Penetration,Inventory Supply,and Financial Performance

Realizing potential benefits from emerging market penetration requires firms to address inherent supply chain challenges. A major challenge is for firms to manage costly inventories to address demand and supply risks in emerging markets. However, emerging market penetration may offer opportunities for firms to lower inventory levels, reduce costs, and improve operating performance. Using data for 482 manufacturing firms over the 5‐year period, 2003–2007, obtained from the COMPUSTAT Industrial and Segment Databases, this article examines the relationships between emerging market penetration, inventory supply, and financial performance. Our results show that a multinational firm's sales penetration into emerging markets is associated with fewer days of inventory supply and improved financial performance. As emerging market penetration may allow firms to operate with lower inventory supply, the positive effect from emerging market penetration, such as labor cost reductions, may be enhanced due to inventory cost savings.     

基于权变视角的管理者社会关系对企业绩效的影响研究

基于动态能力理论和权变研究视角,构建管理者关系、资源整合、创业导向与绩效间关系的理论模型,并利用大规模样本对所提假设进行检验.结果表明,商业关系和政治关系均能提升企业绩效;不同资源整合过程以不同方式调节管理者关系对企业绩效的影响;创业导向对资源整合的调节效应产生深层调节效果.