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。     

Re‐framing the Analysis: A 3‐dimensional Perspective of Prisoners’ Children's Well‐being

This article highlights three dimensions to understanding children's well‐being during and after parental imprisonment which have not been fully explored in current research. A consideration of ‘time’ reveals the importance of children's past experiences and their anticipated futures. A focus on ‘space’ highlights the impact of new or altered environmental dynamics. A study of ‘agency’ illuminates how children cope within structural, material and social confines which intensify vulnerability and dependency. This integrated perspective reveals important differences in individual children's experiences and commonalities in broader systemic and social constraints on prisoners’ children. The paper analyses data from a prospective longitudinal study of 35 prisoners’ children during and after their (step) father's imprisonment to illustrate the arguments.     

Inferences on the Means of Two Log-Normal Distributions: A Computational Approach Test

In this article, we propose a novel approach for testing the equality of two log-normal populations using a computational approach test (CAT) that does not require explicit knowledge of the sampling distribution of the test statistic. Simulation studies demonstrate that the proposed approach can perform hypothesis testing with satisfying actual size even at small sample sizes. Overall, it is superior to other existing methods. Also, a CAT is proposed for testing about reliability of two log-normal populations when the means are the same. Simulations show that the actual size of this new approach is close to nominal level and better than the score test. At the end, the proposed methods are illustrated using two examples.     

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.     

疲劳裂纹扩展试验裂纹图像采集系统

针对目前金属疲劳裂纹扩展检测方法存在效率低、操作繁琐、精度不高，不能实现实时性等缺点，文章提出了基 于机器视觉的裂纹检测方法。根据金属疲劳裂纹扩展试验过程中裂纹图像的采集要求，设计了摄像头位置可自动调整 的疲劳裂纹图像采集系统，包括摄像头安装运动装置，裂纹图像采集装置以及摄像头运动控制系统。图像采集装置由高 分辨率黑白面阵CCD摄像头、光学镜头，光源照明装置和图像采集卡组成，前3者安装在摄像头支架上，与摄像头运动 装置相连。摄像头运动装置中的X，Y，，Z轴运动机构由步进电机带动滚珠导轨机构。在基于ARM技术的运动控制系统 的控制下摄像头可沿X，Y，，Z轴作高精度直线运动，实现和试件之间精确位置的调整。实验结果表明，所设计的系统可 采集到疲劳裂纹扩展试验过程中高清晰度、高分辨率的试件裂纹图像，满足下一步裂绞尺寸计算的要求；摄像头运动定 位精度可达到0. 02 mm，满足精确的系统聚焦、位置调整、跟踪采集的要求。     

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.     

Tests for time series of counts based on the probability-generating function

We propose testing procedures for the hypothesis that a given set of discrete observations may be formulated as a particular time series of counts with a specific conditional law. The new test statistics incorporate the empirical probability-generating function computed from the observations. Special emphasis is given to the popular models of integer autoregression and Poisson autoregression. The asymptotic properties of the proposed test statistics are studied under the null hypothesis as well as under alternatives. A Monte Carlo power study on bootstrap versions of the new methods is included as well as real-data examples.     

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