局部平稳部分线性面板数据模型的统计推断

部分线性模型是一类非常重要的半参数回归模型,由于它既含有参数部分又含有非参数部分,与常规的线性模型相比具有更强的适应性和解释能力。文章研究带有局部平稳协变量的固定效应部分线性面板数据模型的统计推断。首先提出一个两阶段估计方法得到模型中未知参数和非参数函数的估计,并证明估计量的渐近性质,然后运用不变原理构造出非参数函数的一致置信带,最后通过数值模拟研究和实例分析验证了该方法的有效性。     

Testing equality of two normal covariance matrices with monotone missing data

Abstract

The problem of testing equality of two multivariate normal covariance matrices is considered. Assuming that the incomplete data are of monotone pattern, a quantity similar to the Likelihood Ratio Test Statistic is proposed. A satisfactory approximation to the distribution of the quantity is derived. Hypothesis testing based on the approximate distribution is outlined. The merits of the test are investigated using Monte Carlo simulation. Monte Carlo studies indicate that the test is very satisfactory even for moderately small samples. The proposed methods are illustrated using an example.     

“动物与人”：叙事伦理、悖反性与双重困境指向——论“抉择之痛”作为功能指涉的效力边际

对初始情境中受难者“陷困”功能的探讨，是“动物叙事”叙事语法研究中不容忽视的一环，其中贯穿了一个最为基础的叙事功能指向——“抉择之痛”。强调“动物与人”两类受难者角色在身体、心理抑或情感维度陷入某种矛盾与纠结的状态，并且彼此间时常呈现出一定的矛盾悖反性。这一角色身份由动物形象与人类形象分别或共同承担，均指向一种叙事伦理层面的现代境遇的表达。在题材范畴方面，这一功能指涉涵盖了家养类与野生类“动物叙事”各自的叙事范畴。其效力边际已不仅仅局限在单纯生态视域与人性指涉的层面，而是凸显现代语境下人类所面临的共通性的伦理困境：一种挥之不去的矛盾、困惑与不安的情感和心境的写照。     

伸展构造背景下倾角资料的构造解释

系统总结了在伸展构造背景下，导致反映构造特征的地层倾角模式复杂化的多种因素。沉积相的不同、岩性变化、井眼状况和测井作业时间等多种因素都可能使地层倾角资料复杂化。进一步指出在拉张盆地中，进行倾角资料的构造解释，必须了解其构造样式的多样性和复杂性，解释存在的多解性。重点解剖了铲式断层在横剖面情况下，对于不同构造位置下的倾角模式。详细分析了一个倾角模式对应多种构造样式的倾角构造解释实例。倾角资料的构造解释应是综合解释，既要综合井筒的相关地质资料，又要综合测井与地质知识，还必须考虑综合地震资料。     

Random effects regression mixtures for analyzing infant habituation

Random effects regression mixture models are a way to classify longitudinal data (or trajectories) having possibly varying lengths. The mixture structure of the traditional random effects regression mixture model arises through the distribution of the random regression coefficients, which is assumed to be a mixture of multivariate normals. An extension of this standard model is presented that accounts for various levels of heterogeneity among the trajectories, depending on their assumed error structure. A standard likelihood ratio test is presented for testing this error structure assumption. Full details of an expectation-conditional maximization algorithm for maximum likelihood estimation are also presented. This model is used to analyze data from an infant habituation experiment, where it is desirable to assess whether infants comprise different populations in terms of their habituation time.     

On a class exhibiting trend change in average failure rate

Abstract

Weak convergence and moment convergence issues are investigated for the New Better than Average Failure Rate (NBAFR) family (introduced by Loh (1984 Loh, W. Y. 1984. A new generalization of the class of NBU distributions. IEEE Transactions on Reliability R-33 :97–113[Crossref], [Web of Science ®] , [Google Scholar])). We explore the validity of these results in the context of a more general ageing class that we introduce. We prove some new properties of this class and derive its interrelationships with other non-monotonic ageing families. Reliability and moment bounds are obtained and an interesting characterization of exponentiality is proved. Special cases of our results lead to new theorems for the NBAFR class. Finally weak convergence and related issues are established for this class.     

Hill estimator of projections of functional data on principal components

Functional principal component scores are commonly used to reduce mathematically infinitely dimensional functional data to finite dimensional vectors. In certain applications, most notably in finance, these scores exhibit tail behaviour consistent with the assumption of regular variation. Knowledge of the index of the regular variation, α, is needed to apply methods of extreme value theory. The most commonly used method of the estimation of α is the Hill estimator. We derive conditions under which the Hill estimator computed from the sample scores is consistent for the tail index of the unobservable population scores.     

零售4.0时代先行发货问题的大数据分析

在零售4.0时代，渠道的多样化不仅丰富了数据源，还能迅速生成大量数据，需要通过分析大数据，为决策提取有意义的信息，通过分析先行发货的重要性，提出了一种基于遗传算法（GA）的优化模型，预测顾客何时购买，然后在顾客线下单前将产品运送到距顾客最近的配送中心，解决先行发货中存在的问题。研究认为，需要先部署云计算来存储所有渠道生成的大数据，再应用基于集群的关联规则挖掘研究顾客的购买行为，根据“如果-那么”预测规则预测未来的采购情况，最后利用修正的遗传算法生成最优的先行发货计划；这种遗传算法考虑了其在运输成本和运输距离之外，还有预测规则的置信度，利用大量的数值实验权衡了先行发货中的不同因素，验证了模型的最优可靠性     

论数字货币的私法性质——以日本Bitcoin.Cafe数字货币交易所破产案为中心

数字货币，是一种具有财产性价值属性的电磁记录型数据。数字货币在其依存的区块链体系中所彰显的与不特定者之间的支付对价性、与法定货币之间的互换性、使用电子信息处理系统进行转移的在线转移性等特点，得以从数据说的角度，将其作为一种数据性财产权在现行法律框架内对其私法性质进行讨论。有鉴于我国民法总则已将数据纳入保护客体的范畴，数字货币作为数据之一种，理应成为一种新型法律客体，在得到法律理论支撑的基础上获得保护。     

虚拟社会与道德构建

随着网络的普及 ,虚拟社会中人们的思想、行为、生存方式都发生了新的变化。虚拟社会具有虚拟性、自由性、开放性、非人性化的特点 ;虚拟社会的自由和民主精神、权利意识和平等意识、自主精神、奉献精神、开放思想为道德建设提供了新的生长点 ,但同时带来了一系列负效应。因此 ,道德建设要采取一系列相应的措施 ,以构造文明虚拟社会