AR-GARCH型残差控制图及其应用研究

受控过程经常呈现出自相关性和波动簇聚性并存的特征.为解决这类过程的监控问题,本文提出ARGARcH型残差控制图,用自回归模型结合残差图解决自相关问题;用受控过程的条件标准差替代无条件标准差,构造控制图的控制线,解决波动簇聚的问题.并结合对股票周收益序列进行监控的实例对该控制图的有效性加以分析.     

基于协方差阵特征结构的新型控制图研究

本文在深入分析现行广义方差类的统计控制图存在的统计监控缺陷的基础上,提出了对多变量过程的协方差阵的特征向量张成的坐标系的一致性进行统计监控的C控制图,以及对特征值构成的椭球体的相似性进行监控的S控制图,有效地提高了对多变量过程的协方差阵的异常变动的统计监控能力。仿真表明,联合使用C控制图、S控制图及常规均值T²控制图,能够实现对多变量过程的协方差阵与均值的系统监控,显著改善监控效率。     

基于调整型抽样的np控制图设计

在计件型质量控制中np控制图是主要工具之一.然而传统的np控制图由于其对工序变化反应不敏感,已很难适应竞争激烈的现代工业.因而提出一种能充分利用检测信息以及更敏感地反映过程的微小偏移的控制图成为一种迫切的需求.本文正是在这种背景下,提出了一种基于调整型抽样的np控制图,并且利用Markov链分析了其经济性能.     

多资产的股票挂钩保本型理财产品定价研究

结构性理财产品定价的核心问题是收益函数的确定,定价技术难点在于资产相关性的处理.应用Cholesky分解方法,先解决资产间的相关性问题,然后针对多资产保本型股票挂钩结构性产品收益函数特点,利用蒙特卡罗方法对其进行定价.最后以深圳商业银行盈丰理财0706号为例,介绍该方法的应用.结果表明,该产品定价偏高,产品实际收益率偏低.     

中国股市波动性与成交量共同的长期记忆性研究

研究了上证30指数和深圳成分指数所含个股的成交量与收益波动性的长程相关关系.文章应用多变量频域两步半参数估计方法,辅助数据加窗技术对非平稳时间序列的长期记忆性进行了一致有效的估计.研究结果发现中国股票市场的成交量和波动性均具有显著的长期记忆性,并且对于大多数股票而言,成交量序列与波动性序列具有相同的长期记忆性.表明同时驱动成交量和收益波动性的潜在信息流本身具有长期记忆特征.     

自相关过程的统计控制状态

对过程实施统计质量控制的基本假设前提是观测值彼此统计独立,但是实际工作中经常出现过程的观测值存在自相关的现象.本文在简单介绍残差控制图的基础上,探讨了自相关过程的统计控制状态的含义,提出了判断自相关过程是否处于统计控制状态并进而寻找处于统计控制状态下的自相关过程的模型的途径,运用示例加以说明.最后给出保持自相关过程的统计控制状态的方法.     

浅谈图论中着色问题的应用

图论[Graph Theory]是数学的一个分支.它以图为研究对象.给定一个图,如果要求把所有顶点涂上颜色,使得相邻顶点具有不同的颜色,问最少需要几种不同的颜色?这个问题叫做图的点着色问题.由于着色问题反映了广泛而深刻的实际背景,它的研究带动了整个图论的发展.如今图着色的理论被广泛利用于解决安排会议或考试的日程以避免冲突和安排化学品的存储以避免互相反应等具体问题上.下面举例加以说明.     

基于最大熵分布的控制图改进与评价研究

传统的控制图多是假定质量特性参数服从正态分布，但在很多情况下正态分布的假设并不成立。本文基于最大熵分布从控制图的构建和评价两个方面分别提出对Shewhart控制图和CUSUM控制图的改进方法。首先根据"经济性"原则构建最大熵Shewhart控制图，实现对Shewhart控制图的改进；然后，提出结合最大熵分布和马尔科夫链方法的CUSUM控制图评价方法。仿真结果表明，基于最大熵分布改进后的Shewhart控制图控制性能优于改进之前的情况；而基于最大熵分布的CUSUM控制图的性能评价方法得到的结果能更符合真实的情况。在对不同偏移的监测中，最大熵Shewhart控制图更适用于分布未知的大偏移情况，而自适应CUSUM控制图对小偏移有更好地监控效果。     

基于时间序列与机器算法的工商银行股票预测分析

股票市场在国家经济发展中发挥着重要作用,对于投资者来说,其有可能获得超额收益,也有可能遭受巨大损失。因此,如何合理地对股票未来发展作出预测,是投资者关心的问题。文章基于支持向量机、逻辑回归及BP神经网络3种机器学习算法建立分类预测模型,对工商银行股票下一个交易日的涨跌走势进行分析预测,并使用时间序列ARIMA模型进行预测,综合考虑训练模型,分析比较时间序列模型与机器学习对工商银行股票的预测能力。     

中国股票关联网络拓扑性质与聚类结构分析

复杂网络理论是研究股票市场内在结构和功能的有力工具,股票关联网络的拓扑性质和聚类结构对于理解网络的形成机制、发生在网络上的动力学行为具有重要意义.以中国上证180指数和深证100指数成分股票为研究标的,运用最小生成树算法和平面最大过滤图算法构建相应的股票关联网络,分析网络的基本拓扑统计性质和聚类结构.实证研究表明,平面最大过滤图关联网络为小世界网络,各关联网络内股票的影响强度服从幂律分布,股票之间存在的异类匹配模式揭示了市场内股票价格波动传导的过程,对最小生成树关联网络和平面最大过滤图关联网络的宗派和派系聚类分析能有效地挖掘股票之间的聚类结构信息,总体上看平面最大过滤图算法优于最小生成树算法,且实证结论对沪深股票市场具有普适性.     

Probabilistic and membership approaches in the construction of control charts for linguistic data

Abstract

Two approaches for constructing control charts for quality assurance when the observations are in the form of linguistic data are presented. Both approaches are based on fuzzy set theory and use fuzzy subsets to model the linguistic terms used to describe product quality. They differ in the interpretation of the control limits and in the procedure used to reduce the fuzzy subsets to scalars for determining the chart parameters. The results obtained with simulated data suggest that, on the basis of sensitivity to process shifts, the control charts for linguistic data perform better than conventional p control charts. The number of linguistic terms used in classifying the observations was found to influence the sensitivity of these control charts. The transformation method used to obtain the representative values and the amount of fuzziness do not seem to affect the performance of either type of control charts.     

Non-Normality and the Design of Control Charts for Averages*

Non-normality has a significant effect on the performance of control charts for averages. The design considerations for a control chart for averages must include recognition of the degree of non-normality of the underlying data. The performance of a control chart may be judged on its ability to correctly identify the probabilities of assignable causes of variation and chance causes of variation in a process. This paper examines the effects of non-normality, as measured by skewness and kurtosis, on the performance, and hence the design, of control charts for averages and provides an alternative method of designing charts for averages of data with non-normal distributions.     

USING RUN-LENGTH DISTRIBUTIONS OF CONTROL CHARTS TO DETECT FALSE ALARMS

Run-length distributions for various statistical process-control charts and techniques for computing them recently have been reported in the literature. The real advantages of knowing the run-length distribution for a process-control chart versus knowing only the associated average-run length of the chart have not been exploited. Our purpose is to use knowledge of the run-length distribution as an aid in deciding if an out-of-control signal is a true signal or merely a false alarm. The ability to distinguish between true and false signals is important, especially in operations where it is costly to investigate the causes of out-of-control conditions. Knowledge of the run-length distribution allows us to compute likelihood ratios, which are simple to calculate and to interpret and which are used to determine the odds of obtaining an out-of-control signal at a particular run length when a shift in the process mean actually has occurred vis-a-vis no such shift. We extend our analysis in a Bayesian sense by incorporating prior information on the distribution of the shift size of the process mean, combined with the likelihood ratio obtained from the run-length distribution, to determine if a shift larger than a critical size has occurred. We give examples for the Shewhart chart, the exponentially weighted moving-average chart, and the special-cause control chart for processes with autocorrelated observations. The examples show that the current recommended usage of the average-run length alone as a guide for determining whether a signal is a false alarm or otherwise can be misleading. We also show that the performance of the traditional charts, in terms of their average-run length, can be enhanced in many instances by using the likelihood-ratio procedure.     

第Ⅱ类拆卸线平衡问题建模及优化

环境资源问题日益凸显、人们环保意识的增强以及经济利益的驱动，促使社会进行废旧产品回收再利用，以发展绿色经济。拆卸作为回收再利用过程中的核心环节，采用流水线的方式组织产品精细化拆卸，可实现资源最大化价值。然而，零部件作业任务在流水线上分配排序过程复杂，各工作站上的作业负荷需保持相对均衡，才能保证拆卸线高效运行。为此，本文在拆卸线工作站数量固定的情况下，以最短节拍时间和均衡任务在工作站上的分配为目标，建立第Ⅱ类拆卸线平衡问题优化模型，并提出一种并行动态邻域深度搜索算法进行求解。所提算法采用动态搜索机制实现解在各邻域结构集内的并行深度搜索；通过设置扰动阈值对解实施干扰，以加快跳出局部最优；在节拍时间调整过程中，采用基于二分法的定界策略，以实现向最优节拍时间的快速靠拢。最后，通过不同规模算例验证了模型的有效性以及算法的高效性。     

对W-B乘子置信域约束构造方法的改进及模型

Wong和Beasley针对数据包络分析(DEA)给出的乘子约束方法(W-B方法)常常会导致相应的模型没有可行解问题。指出了该问题出现的根源在于W-B方法在使用权重重要性概念时存在着逻辑不一致,并提出了一种构造乘子置信域(AR)约束的改进方法及相应的DEA/AR模型。改进方法及模型具有能够克服W-B方法所常常出现的某些乘子置信约束之间相互矛盾问题等三方面优点。经实例应用,验证了所提出的改进方法及相应的DEA/AR模型是切实可行的。     

The Detection of Nuclear Materials Losses*

The identification and location of materials losses in nuclear facilities is an important issue. Many complexities arise in monitoring such losses. These complexities include the dependency among materials balance observations and the influence of errors (outliers) on parameter estimates of various monitoring methods. The proposed Joint Estimation procedure is superior to standard methods (control chart and CUSUM) and to methods that build in correlation (ARMA control chart, ARMA CUSUM, and the Generalized M procedure) in the detection of nuclear materials losses. The Joint Estimation procedure is robust to the influence of outliers, is flexible in accommodating a range of dependencies among observations, and provides information on the type of loss. Further, the procedure is reliable in that it yields a probability of false alarms and a probability of detecting losses closer to specifications.     

Projection‐Based Statistical Inference in Linear Structural Models with Possibly Weak Instruments

It is well known that standard asymptotic theory is not applicable or is very unreliable in models with identification problems or weak instruments. One possible way out consists of using a variant of the Anderson–Rubin ((1949), AR) procedure. The latter allows one to build exact tests and confidence sets only for the full vector of the coefficients of the endogenous explanatory variables in a structural equation, but not for individual coefficients. This problem may in principle be overcome by using projection methods (Dufour (1997), Dufour and Jasiak (2001)). At first sight, however, this technique requires the application of costly numerical algorithms. In this paper, we give a general necessary and sufficient condition that allows one to check whether an AR‐type confidence set is bounded. Furthermore, we provide an analytic solution to the problem of building projection‐based confidence sets from AR‐type confidence sets. The latter involves the geometric properties of “quadrics” and can be viewed as an extension of usual confidence intervals and ellipsoids. Only least squares techniques are needed to build the confidence intervals.     

A harmony search-based memetic optimization model for integrated production and transportation scheduling in MTO manufacturing

This paper investigates an integrated production and transportation scheduling problem in an MTO supply chain. A harmony search-based memetic optimization model is developed to handle this problem, in which certain heuristic procedures are proposed to convert the investigated problem into an order assignment problem. A novel improvisation process is also proposed to improve the optimum-seeking performance. The effectiveness of the proposed model is validated by numerical experiments. The experimental results show that (1) the proposed model can solve the investigated problem effectively and that (2) the proposed memetic optimization process exhibits better optimum-seeking performance than genetic algorithm-based and traditional memetic optimization processes.