Robust multivariate control charts based on Birnbaum–Saunders distributions

Multivariate control charts are powerful and simple visual tools for monitoring the quality of a process. This multivariate monitoring is carried out by considering simultaneously several correlated quality characteristics and by determining whether these characteristics are in control or out of control. In this paper, we propose a robust methodology using multivariate quality control charts for subgroups based on generalized Birnbaum–Saunders distributions and an adapted Hotelling statistic. This methodology is constructed for Phases I and II of control charts. We estimate the corresponding parameters with the maximum likelihood method and use parametric bootstrapping to obtain the distribution of the adapted Hotelling statistic. In addition, we consider the Mahalanobis distance to detect multivariate outliers and use it to assess the adequacy of the distributional assumption. A Monte Carlo simulation study is conducted to evaluate the proposed methodology and to compare it with a standard methodology. This study reports the good performance of our methodology. An illustration with real-world air quality data of Santiago, Chile, is provided. This illustration shows that the methodology is useful for alerting early episodes of extreme air pollution, thus preventing adverse effects on human health.     

Asymmetric matrix-valued covariances for multivariate random fields on spheres

ABSTRACT

Matrix-valued covariance functions are crucial to geostatistical modelling of multivariate spatial data. The classical assumption of symmetry of a multivariate covariance function is overly restrictive and has been considered as unrealistic for most of the real data applications. Despite of that, the literature on asymmetric covariance functions has been very sparse. In particular, there is some work related to asymmetric covariances on Euclidean spaces, depending on the Euclidean distance. However, for data collected over large portions of planet Earth, the most natural spatial domain is a sphere, with the corresponding geodesic distance being the natural metric. In this work, we propose a strategy based on spatial rotations to generate asymmetric covariances for multivariate random fields on the d-dimensional unit sphere. We illustrate through simulations as well as real data analysis that our proposal allows to achieve improvements in the predictive performance in comparison to the symmetric counterpart.     

Quantile-based Chernoff distance for truncated random variables

Several probability distributions such as power-Pareto distribution (see Gilchrist 2000 Gilchrist, W. 2000. Statistical modelling with quantile functions. Boca Raton, FL: Chapman and Hall/CRC.[Crossref] , [Google Scholar] and Hankin and Lee 2006 Hankin, R. K. S., and A. Lee. 2006. A new family of non-negative distributions. Australian and New Zealand Journal of Statistics 48:67–78.[Crossref], [Web of Science ®] , [Google Scholar]), various forms of lambda distributions (see Ramberg and Schmeiser 1974 Ramberg, J. S., and B. W. Schmeiser. 1974. An appropriate method for generating asymmetric random variables. Communications of the ACM 17:78–82.[Crossref], [Web of Science ®] , [Google Scholar] and Freimer et al. 1988 Freimer, M., S. Mudholkar, G. Kollia, and C. T. Lin. 1988. A study of the generalized lambda family. Communications in Statistics - Theory and Methods 17:3547–67.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]), Govindarajulu distribution (see Nair, Sankaran, and Vineshkumar 2012 Nair, U. N., P. G. Sankaran, and B. Vineshkumar. 2012. The Govindarajulu distribution: some properties and applications. Communications in Statistics—Theory and Methods 41:4391–406.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]), etc., do not have manageable distribution functions, though they have tractable quantile functions. Hence, analytical study of the properties of Chernoff distance of two random variables associated with these distributions via traditional distribution function-based tool becomes difficult. To make this simple, in this paper, we introduce quantile-based Chernoff distance for (left or right) truncated random variables and study its various properties. Some useful bounds as well as characterization results are obtained.     

Model averaging for multivariate multiple regression models

The theories and applications of model averaging have been developed comprehensively in the past two decades. In this paper, we consider model averaging for multivariate multiple regression models. In order to make use of the correlation information of the dependent variables sufficiently, we propose a model averaging method based on Mahalanobis distance which is related to the correlation of the dependent variables. We prove the asymptotic optimality of the resulting Mahalanobis Mallows model averaging (MMMA) estimators under certain assumptions. In the simulation study, we show that the proposed MMMA estimators compare favourably with model averaging estimators based on AIC and BIC weights and the Mallows model averaging estimators from the single dependent variable regression models. We further apply our method to the real data on urbanization rate and the proportion of non-agricultural population in ethnic minority areas of China.     

An extension of the relaxation algorithm for solving a special case of capacitated arc routing problems

In this paper, we propose an exact method for solving a special integer program associated with the classical capacitated arc routing problems (CARPs) called split demand arc routing problems (SDARP). This method is developed in the context of monotropic programming theory and bases a promising foundation for developing specialized algorithms in order to solve general integer programming problems. In particular, the proposed algorithm generalizes the relaxation algorithm developed by Tseng and Bertsekas (Math. Oper. Res. 12(4):569–596, 1987) for solving linear programming problems. This method can also be viewed as an alternative for the subgradient method for solving Lagrangian relaxed problems. Computational experiments show its high potential in terms of efficiency and goodness of solutions on standard test problems.     

社会互动视角下驱动消费者绿色购买的社会机制研究

绿色购买不仅受到与环境相关的内部心理因素的促进作用,还受到与社会互动相关的外部情境因素的驱动作用。基于社会互动理论视角,聚焦于社会规范中的命令性规范,构建了绿色购买的社会机制。通过两组实验研究发现,相比普通环保信息,命令性规范信息增强消费者的绿色购买意愿;社会价值中介两者之间的关系;社会距离调节命令性规范信息对社会价值的影响,并调节社会价值的中介作用,在远社会距离情境下,消费者感知到更多的社会价值,但社会价值的中介作用比近社会距离情境要弱。基于此,提出政府应在全社会营造浓厚的绿色消费社会互动氛围,并提出了具体的企业营销措施。     

FDI对产业结构调整的影响

基于东北三省2006—2016年动态面板数据,建立固定效应模型和面板VAR模型,利用Stata软件引入人力资本变量,实证分析三省FDI对产业结构调整的影响。研究结果表明:东北三省FDI变量对产业结构变量影响减弱,且有负面影响趋势。由于FDI变量使用的是相对值,实证结果不能说明其对产业结构调整存在负面影响,但说明了FDI对产业结构调整的作用在弱化。引入人力资本作为技术进步的代理变量,实证分析得出人力资本对产业结构存在正向作用的结论,说明人力资本显著促进了产业结构调整。     

Minimum-distance methods based on quadratic distances for transforms

A class of minimum-distance methods based on empirical transforms is considered. This class includes the minimum-chi-squared method, the K-L method for empirical characteristic functions, and the analogous method for empirical moment generating functions. Asymptotic properties of the minimum-distance estimators and goodness-of-fit test statistics are derived. A general analogue of the Rao-Robson statistic is formulated.     

实施企业资源计划管理提高企业经济效益

企业资源计划是目前我国许多企业在运营中所采用的一项技术。这项技术在企业管理中有许多积极功能。要正确实施这项技术必须制定出企业资源计划系统的标准业务流程。