On the α-risks for shewhart control charts

The performance of the usual Shewhart control charts for monitoring process means and variation can be greatly affected by nonnormal data or subgroups that are correlated. Define the α_k-risk for a Shewhart chart to be the probability that at least one “out-of-control” subgroup occurs in k subgroups when the control limits are calculated from the k subgroups. Simulation results show that the α_k-risks can be quite large even for a process with normally distributed, independent subgroups. When the data are nonnormal, it is shown that the α_k-risk increases dramatically. A method is also developed for simulating an “in-control” process with correlated subgroups from an autoregressive model. Simulations with this model indicate marked changes in the α_k-risks for the Shewhart charts utilizing this type of correlated process data. Therefore, in practice a process should be investigated thoroughly regarding whether or not it is generating normal, independent data before out-of-control points on the control charts are interpreted to be due to some real assignable cause.     

NONPARAMETRIC TWO SAMPLE TESTS BASED ON AREA STATISTICS

ABSTRACT

Area statistics are sample versions of areas occurring in a probability plot of two distribution functions F and G. This paper presents a unified basis for five statistics of this type. They can be used for various testing problems in the framework of the two sample problem for independent observations, such as testing equality of distributions against inequality or testing stochastic dominance of distributions in one or either direction against nondominance. Though three of the statistics considered have already been suggested in literature, two of them are new and deserve our interest. The finite sample distributions of the statistics (under F=G) can be calculated via recursion formulae. Two tables with critical values of the new statistics are included. The asymptotic distribution of the properly normalized versions of the area statistics are functionals of the Brownian bridge. The distribution functions and quantiles thereof are obtained by Monte Carlo simulation. Finally, the power functions of the two new tests based on area statistics are compared to the power functions of the tests based on the corresponding supremum statistics, i.e., statistics of the Kolmogorov–Smirnov type.     

The Continuum of Care System

Abstract

The Continuum of Care System is a Decision Support System designed to assist social workers responsible for identifying and selecting alternative living arrangements for children unable to remain in their own families. The Continuum of Care System consists of two software packages called MATCH and PROFILE. MATCH produces a rank-ordered list of prospective placement alternatives by statistically comparing an individual child to groups of children previously admitted into different residential facilities. PROFILE summarizes the characteristics and problems of children at each facility in the system.     

A generalization of the compound rayleigh distribution: using a bayesian method on cancer survival times

In this paper the generalized compound Rayleigh model, exhibiting flexible hazard rate, is high¬lighted. This makes it attractive for modelling survival times of patients showing characteristics of a random hazard rate. The Bayes estimators are derived for the parameters of this model and some survival time parameters from a right censored sample. This is done with respect to conjugate and discrete priors on the parameters of this model, under the squared error loss function, Varian's asymmetric linear-exponential (linex) loss function and a weighted linex loss function. The future survival time of a patient is estimated under these loss functions. A Monte Carlo simu¬lation procedure is used where closed form expressions of the estimators cannot be obtained. An example illustrates the proposed estimators for this model.     

中国法治政府的演化博弈模型构建

演化博弈论在中国法治政府研究中具有很好的适用性,可以据此构建“复制动态”的中国法治政府的演化博弈模型,证明“内生演化”的法治能够从根本上解决政府“权力悖论”。中国法治政府建设需要围绕约束规范公权力的主题,确立互动平衡精神和采取渐进主义策略,以改进转型中国的法治秩序。     

桥塞坐封过程仿真模拟研究

桥塞作为井下封层技术的关键设备,由于它施工工序少、周期短、卡封位置准确而得到了广泛应用。针对设计的可钻式非金属桥塞坐封过程开展模拟研究,涉及弹塑性材料接触、超弹性材料接触和非金属材料动态断裂的非线性动力学问题,利用有限元法建立该桥塞全尺寸模型和所有部件之间的广义接触关系,通过有限元模拟动态坐封过程获得桥塞各部件运动变形特性、桥塞与套管之间的密封特性和动态坐封力等数据,该桥塞坐封完成时,坐封机构部件轴向位移110 mm,坐封力约45 kN。模拟坐封也为进一步优化该型桥塞的结构和评估坐封性能提供了理论依据,对该型桥塞的推广应用奠定了基础。     

基于正交试验的长条薄壁板件注塑工艺参数优化与定量分析

针对塑件成型过程中体积收缩率对成型塑件尺寸精度的影响,文章选取长条薄壁板件作为研究对象,利用AMI有限元分析软件对长条薄壁板注塑成型过程进行数值模拟,采用多因素交互正交试验的方法获得常用ABS塑料在不同的工艺参数下成型薄壁件的体积收缩率。以体积收缩率为研究目标,对试验结果进行定量分析,对比分析每一个工艺参数对研究目标的贡献率,并计算得到最优的工艺参数组合,依据实验结果优化塑件成型工艺。该方法的应用为注塑成型工艺参数优化提供了定量的数据参考,是一种快速而实用的方法。     

食品检测咀嚼机器人工作空间研究

为了提高食品检测效率,改善食品检测精度,增加食品检测的客观性,文章介绍了一种基于6-UPS机构的咀嚼机器人,介绍了咀嚼机器人的结构原理,求解了机构的运动学逆解,分析了机构的工作空间影响因素,利用MATLAB编程求得机构在定姿态下的工作空间。空间轮廓图表明,该机构在定姿态下能到达人类全部真实咀嚼空间,机构设计可靠,能够模拟人类咀嚼行为对食品进行检测。     

Mixed-effects Models with Skewed Distributions for Time-varying Decay Rate in HIV Dynamics

After initiation of treatment, HIV viral load has multiphasic changes, which indicates that the viral decay rate is a time-varying process. Mixed-effects models with different time-varying decay rate functions have been proposed in literature. However, there are two unresolved critical issues: (i) it is not clear which model is more appropriate for practical use, and (ii) the model random errors are commonly assumed to follow a normal distribution, which may be unrealistic and can obscure important features of within- and among-subject variations. Because asymmetry of HIV viral load data is still noticeable even after transformation, it is important to use a more general distribution family that enables the unrealistic normal assumption to be relaxed. We developed skew-elliptical (SE) Bayesian mixed-effects models by considering the model random errors to have an SE distribution. We compared the performance among five SE models that have different time-varying decay rate functions. For each model, we also contrasted the performance under different model random error assumptions such as normal, Student-t, skew-normal, or skew-t distribution. Two AIDS clinical trial datasets were used to illustrate the proposed models and methods. The results indicate that the model with a time-varying viral decay rate that has two exponential components is preferred. Among the four distribution assumptions, the skew-t and skew-normal models provided better fitting to the data than normal or Student-t model, suggesting that it is important to assume a model with a skewed distribution in order to achieve reasonable results when the data exhibit skewness.