We are not walking wave functions. A response to “Quantum Mind and Social Science” by Alexander Wendt

Alexander Wendt raises many interesting questions in this book, but to get to the answers he wants, he relies on a misunderstanding of the nature of the quantum states of macroscopic objects.     

一种改进型专家模糊核聚类赋权方法研究

针对传统基于判断矩阵的专家模糊核聚类赋权方法，由于归一化条件的制约，导致离群点对聚类结果产生不良影响的问题，提出一种改进型模糊核聚类算法。该方法在聚类过程中，通过放宽归一化约束条件，削弱离群点对聚类结果的影响；并且针对传统基于信息熵与一致性系数线性耦合的聚类标准的局限性，提出一种基于偏差熵的赋权方法，依据专家对自身类别的聚类贡献度，确定专家权重，克服了传统方法的不足。算例表明，该方法可行、有效。     

马克思漠视熵定律吗？——生态经济学与生态马克思主义的论争

以阿里尔为代表的生态经济学家与以福斯特、伯克特为代表的生态马克思主义者,就马克思与熵的关系问题展开了批判与反批判的深度交锋。鉴于熵定律在生态经济学中的重要作用,阿里尔批判了马克思对熵定律的漠视,指责其忽视了自然条件对人类经济社会生活的限制。对此,福斯特、伯克特展开了反批判,论述了马克思将热力学应用到劳动力价值的形成和剩余价值的创造的分析中,并借此阐释了马克思主义之于生态经济学的多重意义。福斯特、伯克特是以历史唯物主义的方法论,反对将生态环境问题作能量还原论的阐释,并借此阐述了马克思的“新陈代谢—热力学”思想,进一步夯实了马克思主义生态学何以可能的学理支撑。     

“一带一路”建设中广东区域城市群协调发展研究

以“一带一路”建设中广东区域城市群为研究对象,选取经济、社会和环境3个系统构建指标体系,运用改进熵值法、耦合协调度函数及综合协调发展度模型等进行实证分析,得出结论:广东区域城市群综合协调发展情况总体较好,但城市之间差距较大;提高经济与社会发展指数迫在眉睫,广东21个城市中,经济、社会与环境三大子系统均衡发展的城市1个,某个子系统发展指数滞后的城市6个,经济与社会发展指数滞后的城市14个;珠三角地区各城市协调等级全部属于协调类,从协调度评价结果分布来看,已经形成梯度发展的态势;粤东城镇群、粤西城镇群和韶关都市区协调度和协调类型明显逊色。依据此结论,论述了广东参与“一带一路”建设应以珠江三角洲区域经济一体化为核心,落实振兴粤东西北地区的政策,各区域城市应结合自身特点加以调整发展,利用“一带一路”的政策红利和战略机遇提升城市协调度的观点。     

Beta-Bernstein Smoothing for Regression Curves with Compact Support

ABSTRACT. The problem of boundary bias is associated with kernel estimation for regression curves with compact support. This paper proposes a simple and uni(r)ed approach for remedying boundary bias in non-parametric regression, without dividing the compact support into interior and boundary areas and without applying explicitly different smoothing treatments separately. The approach uses the beta family of density functions as kernels. The shapes of the kernels vary according to the position where the curve estimate is made. Theyare symmetric at the middle of the support interval, and become more and more asymmetric nearer the boundary points. The kernels never put any weight outside the data support interval, and thus avoid boundary bias. The method is a generalization of classical Bernstein polynomials, one of the earliest methods of statistical smoothing. The proposed estimator has optimal mean integrated squared error at an order of magnitude n ^−4/5, equivalent to that of standard kernel estimators when the curve has an unbounded support.     

Multivariate bandwidth selection for local linear regression

The existence and properties of optimal bandwidths for multivariate local linear regression are established, using either a scalar bandwidth for all regressors or a diagonal bandwidth vector that has a different bandwidth for each regressor. Both involve functionals of the derivatives of the unknown multivariate regression function. Estimating these functionals is difficult primarily because they contain multivariate derivatives. In this paper, an estimator of the multivariate second derivative is obtained via local cubic regression with most cross-terms left out. This estimator has the optimal rate of convergence but is simpler and uses much less computing time than the full local estimator. Using this as a pilot estimator, we obtain plug-in formulae for the optimal bandwidth, both scalar and diagonal, for multivariate local linear regression. As a simpler alternative, we also provide rule-of-thumb bandwidth selectors. All these bandwidths have satisfactory performance in our simulation study.     

Adaptive normal reference bandwidth based on quantile for kernel density estimation

Bandwidth selection is an important problem of kernel density estimation. Traditional simple and quick bandwidth selectors usually oversmooth the density estimate. Existing sophisticated selectors usually have computational difficulties and occasionally do not exist. Besides, they may not be robust against outliers in the sample data, and some are highly variable, tending to undersmooth the density. In this paper, a highly robust simple and quick bandwidth selector is proposed, which adapts to different types of densities.     

Estimation using plug-in of the stationary distribution and Shannon entropy of continuous time Markov processes

A natural way to deal with the uncertainty of an ergodic finite state space Markov process is to investigate the entropy of its stationary distribution. When the process is observed, it becomes necessary to estimate this entropy.We estimate both the stationary distribution and its entropy by plug-in of the estimators of the infinitesimal generator. Three situations of observation are discussed: one long trajectory is observed, several independent short trajectories are observed, or the process is observed at discrete times. The good asymptotic behavior of the plug-in estimators is established. We also illustrate the behavior of the estimators through simulation.     

基于购买行为RFM及评论行为RFMP模型的客户终身价值研究

在Web2.0时代,越来越多的消费者在购物网站、点评类网站以及社交类网站上发表自己对产品或服务的相关看法,由此对企业产生了巨大的影响。针对用户在线评论行为所产生的价值,以传统的RFM模型为基础构建了基于评论行为的RFMP模型。同时将购买RFM和评论RFMP模型进行结合,提出了适用于线上企业的客户终身价值评价方法,采用熵值法进行了指标权重的确定,并最终选取大众点评网的实际用户数据进行了传统客户终身价值与改进客户终身价值的对比。通过对用户群进行细分,为企业提供了更加精准的营销决策及管理建议。