On hysteretic vector autoregressive model with applications

This paper proposes a new hysteretic vector autoregressive (HVAR) model in which the regime switching may be delayed when the hysteresis variable lies in a hysteresis zone. We integrate an adapted multivariate Student-t distribution from amending the scale mixtures of normal distributions. This HVAR model allows for a higher degree of flexibility in the degrees of freedom for each time series. We use the proposed model to test for a causal relationship between any two target time series. Using posterior odds ratios, we overcome the limitations of the classical approach to multiple testing. Both simulated and real examples herein help illustrate the suggested methods. We apply the proposed HVAR model to investigate the causal relationship between the quarterly growth rates of gross domestic product of United Kingdom and United States. Moreover, we check the pairwise lagged dependence of daily PM2.5 levels in three districts of Taipei.     

Robust inference for estimating equations with nonignorably missing data based on SIR algorithm

Nonresponse is a very common phenomenon in survey sampling. Nonignorable nonresponse – that is, a response mechanism that depends on the values of the variable having nonresponse – is the most difficult type of nonresponse to handle. This article develops a robust estimation approach to estimating equations (EEs) by incorporating the modelling of nonignorably missing data, the generalized method of moments (GMM) method and the imputation of EEs via the observed data rather than the imputed missing values when some responses are subject to nonignorably missingness. Based on a particular semiparametric logistic model for nonignorable missing response, this paper proposes the modified EEs to calculate the conditional expectation under nonignorably missing data. We can apply the GMM to infer the parameters. The advantage of our method is that it replaces the non-parametric kernel-smoothing with a parametric sampling importance resampling (SIR) procedure to avoid nonparametric kernel-smoothing problems with high dimensional covariates. The proposed method is shown to be more robust than some current approaches by the simulations.     

基于多标准的ABC分类库存模型

ABC分类库存方法是企业应用最广泛的库存分类方法之一。国内外学者在研究ABC库存分析法时通常只针对一种分类标准,然而按照多种标准进行分类的库存模型则研究的相对较少。提出了一种新型的基于多标准的ABC分类库存模型,此模型概括了线性和非线性的情况,重点研究库存物品权重在分类中的影响作用。通过对比本模型与AHP方法所得出的结果,然后进行数据整理、对比分析,得出了库存物品的权重在分类决策中占有非常重要的地位。最后,通过数据证明得到此研究方法在库存决策方面更优,能够更好地为库存管理者提供决策依据。     

北京地区农村电力消费模型研究

基于北京农村地区用电消费的实际调查,我们发现农村地区的用电与家庭户均支出、电冰箱保有率、空调拥有率、电热毯保有率有较为密切的相关关系,本文对北京地区的农村用电消费建立了一个研究模型,以此指导农村地区用电市场的开发与建设。     

Another economy: towards a cultural dialectics between energy and society

The looming oil crisis, pollution, and climate change have pushed governments, corporations, and individuals to think of new policies, new objects/products and new manners to market them – usually under the label of “green economy” (or the shifting towards a sustainable economy).

The changes that are on the way as a result of the envisaged “green revolution” need a broad vision that couples the economy of energetic techniques with the related socio-cultural economy that is induced by, and at the same time reciprocally influences, the mere technical transformations.

Based on previous analysis of theories of socio-technological change and putting at its center the concept of subjectivation in social sciences, this article proposes a theoretical understanding of cultural shifts and their relationship with changes in the practices of production, transfer and use of energy.

First part presents a schema of subjectivation in triangulation, that links the biological level with the material culture and with the representational realm of normativities in our society. It will be developed through the example of electric vehicle as metaphor of the energetic transition. Through this understanding, second part deals with the modeling of the three items as a processual energetic system by using the concepts of surplus and expenditure. Within this frame, we show how disruptions in one of the poles of this model influences the others and bring about changes in the entire Anthropo-Social level. Third part proposes possible types of emerging subjectivities and advances the idea of extending the realm of consciousness to the energetic transfers and their potentiality.     

非对称成本扰动信息非线性需求函数下的供应链契约设计

为了分析非对称的成本扰动信息对于供应链契约设计的影响,研究了当制造商的成本发生扰动并且扰动信息是非对称的情形下的零售商的最优契约设计问题。假定市场需求是关于价格的非线性函数,使用委托-代理理论,设计了非对称的成本扰动信息下的供应链最优契约菜单,并且分析了非对称的扰动信息对于供应链绩效的影响。研究结果表明,当需求为常数柔性函数或者指数函数形式时,可以设计有效的契约菜单来改善供应链的绩效;在非对称的成本扰动信息下,当生产成本扰动满足一定条件时,初始的生产计划仍然是最优的;非对称的成本扰动信息并不必然会给供应链带来利润损失。最后通过数值算例对模型的结果进行了验证。     

基于贝叶斯正则化的TDBPNN模型在中国外贸预报中的应用及评估

基于相空间重构的非线性预报思想,建立一个时滞的BP神经网络模型(TDBPNN),采用贝叶斯正则化方法提高BP网络的泛化能力,并将该模型应用于中国进出口贸易的预测,结果证明改进的TDBPNN模型具有较好的泛化能力,准确拟合了进出口贸易发展的历史值和趋势。区别于一般的预测评价,认为非线性预测不仅要注重数据拟合和精度改进,而且应该能够反映被预报系统的非线性特征。在分析模型预测精度的同时,通过计算拟合序列和原序列的非线性特征量进行模型评价,证实预测模型能够合理地“捕捉”到产生原序列的非线性系统的动力学特征。     

On Approximability of Boolean Formula Minimization

For a Boolean function given by a Boolean formula (or a binary circuit) S we discuss the problem of building a Boolean formula (binary circuit) of minimal size, which computes the function g equivalent to , or -equivalent to , i.e., . In this paper we prove that if P NP then this problem can not be approximated with a good approximation ratio by a polynomial time algorithm.     

非线性需求下具有网络外部性的二级歧视定价研究

研究了非线性需求函数条件下产品存在网络外部性时,垄断企业采用对需求区间分段定价的方法进行二级歧视定价的策略。首先分析了单阶段垄断企业二级价格歧视的静态定价策略,接着给出了在一个较长时期内垄断企业分两阶段进行二级歧视的动态定价策略。结果表明网络外部性不影响最优需求区间分段单调递增的性质,但价格随网络外部性的增强而相应提高,且第一阶段的价格高于第二阶段的贴现值。     

Agent‐Based Recovery Model for Seismic Resilience Evaluation of Electrified Communities

In this article, an agent‐based framework to quantify the seismic resilience of an electric power supply system (EPSS) and the community it serves is presented. Within the framework, the loss and restoration of the EPSS power generation and delivery capacity and of the power demand from the served community are used to assess the electric power deficit during the damage absorption and recovery processes. Damage to the components of the EPSS and of the community‐built environment is evaluated using the seismic fragility functions. The restoration of the community electric power demand is evaluated using the seismic recovery functions. However, the postearthquake EPSS recovery process is modeled using an agent‐based model with two agents, the EPSS Operator and the Community Administrator. The resilience of the EPSS–community system is quantified using direct, EPSS‐related, societal, and community‐related indicators. Parametric studies are carried out to quantify the influence of different seismic hazard scenarios, agent characteristics, and power dispatch strategies on the EPSS–community seismic resilience. The use of the agent‐based modeling framework enabled a rational formulation of the postearthquake recovery phase and highlighted the interaction between the EPSS and the community in the recovery process not quantified in resilience models developed to date. Furthermore, it shows that the resilience of different community sectors can be enhanced by different power dispatch strategies. The proposed agent‐based EPSS–community system resilience quantification framework can be used to develop better community and infrastructure system risk governance policies.