国家标准《常规控制图》判异准则的问题及其改进——兼谈判异准则的概率计算

探讨了国家标准GB／T4091—2001《常规控制图》（等同采用国际标准ISO8258：1991）判别过程偏离统计控制状态，即发生异常的准则。通过对发生异常的事件的概率的精确计算，发现准则8，即“连续8点在中心线两侧，但无一点在C区中”的发生概率远小于前7个准则所对应的事件的发生概率。建议将该准则改为“连续5点在中心线两侧，但无一点在C区中”，以使对应事件发生的概率与其他准则相匹配。     

政府统计数据质量管理的国际准则

政府统计数据质量管理除了因各国具体的国情不同而在领导和组织的方式上有所差异外,在共同的技术层面上,各国政府统计机构越来越认同或遵循一系列国际准则.这些国际准则都在一定程度上影响着政府统计数据质量及其管理,它们主要分为三个层次,第一个层次是有关统计核算的国际准则,其中主要有<国民经济核算体系>(SNA)、<国际收支手册>(BOP)、<政府财政统计手册>(GFS)和<货币与金融统计手册>(MFS)等,它们给一国宏观经济统计数据的编制提供了理论基础和方法论基础;第二个层次是有关统计数据公布的国际准则,具体包括<数据公布通用系统>(GDDS)和<数据公布特别标准>(SDDS)两个,它们主要对统计数据生产和公布质量方面的规范性进行技术阐释;第三个层次是有关统计数据质量评估框架的国际准则,即IMF制定的统计数据质量评估框架,简称DQAF,它提供了对统计数据质量进行定性评估的基本方法.下面将对这三个层次的国际准则中与政府统计数据质量管理相关的内容分别加以介绍和说明.     

关于统计过程控制中样本组数量的研究

文章首先分析了统计过程控制的理论基础;然后对判稳准则的几种情况进行了显著性水平α的计算,对不同文献中取不同的样本组进行了理论计算和分析。在符合控制图的理论基础和综合考虑现代过程控制的要求前提下,文章建议采用35组样本组作为过程稳态判断的依据。     

视同销售业务的会计处理及纳税调整探析

新<企业会计准则>颁布后,视同销售业务的会计处理发生了很大的变化,<企业所得税法实施条例>中对视同销售业务的所得税缴纳也有了新的规定.……     

关于无形资产计量的几点想法

本文就财政部颁布的<企业会计准则----无形冶资产>(财会[2001]7号)(以下简称<准则>中,关于无形资产的计量问题,谈谈自己的一孔之见.     

六西格玛管理的常规控制图

上一期介绍了SPC与控制图原理,这一期介绍几种常规控制图的制作方法。控制图的分类从控制图绘制的原理看,休哈特(W.A.Shewhart)于1924年提出的采用3原理绘制的控制图称为常规控制图。之后统计工作者又提出了许多其他非常规控制图。本文以下内容介绍常规控制图,非常规控制图在下一期介绍。按照控制图所采用的控制变量的类型划分为计量值控制图和计数值控制图。计量值控制图的控制变量是可以连续计量的,属于连续型随机变量,一般要求其服从正态分布,例如控制变量为长度、温度、时间、电流、电压等;计数值控制图的控制变量是不可以连续计量的…     

中期财务报告的有效性检验

中期财务报告是指除了通常所谓的年度报告之外的以其他时间间隔为基础编制的财务报告.年度报告与中期财务报告的区别,不仅仅在于报告时间间隔的不同,而在于他们在会计要素的确认计量和报告的方式上也存在较大的区别.根据<国际会计准则34号--中期财务报告>,中期是指"短于一个完整的财务年度的财务报告期间",中期财务报告是指"包括涵盖一个中期的一套完整的财务报表,(如<国际会计准则第一号--财务报表>列报所述),或者一套简明的财务报表的财务报告".我国于2001年11月2日发布的<企业会计准则--中期财务报告>则将"中期"和"中期财务报告"分别定义为"短于一个完整的会计年度的报告期间","中期财务报告是指以中期为基础编制的财务报告",与国际会计准则基本相同.     

谈农民工的养老保险问题

随着城市化进程的加快,越来越多的农村劳动力背井离乡,到城市谋生.据农业部统计,2001年全国有7800万农村劳动力外出打工.虽然现在他们的年龄结构还比较年轻,但是20年以后他们的养老问题怎么办?到时候再重新依靠种地务农来养老显然已经不是他们的专长,也不是他们的心愿所在.因此很多人认为应该未雨绸缪,及早做出制度安排.关于无形资产计量的几点想法左湘利本文就财政部颁布的<企业会计准则--无形资产>(财会[2001]7号)(以下简称<准则>)中,关于无形资产的计量问题,谈谈自己的一孔之见.     

残差控制图检测能力分析及效率评价

当质量过程呈现自相关现象时,残差控制图是解决其控制问题的有效方法之一.但是与常规控制图相比较,两者检测性能有很大不同.本文应用检测能力指数和平均链长两种衡量指标,评价了质量过程为AR(1)的残差控制图对异常状态的检测能力.     

关于计算中心建设的几点探讨

随着计算机及网络技术的发展,对计算中心管理的要求越来越高,为了确保计算机系统稳定、安全、可靠地运行,保障计算中心工作人员良好的工作环境,做到技术先进、经济合理、安全适用、确保质量,我国先后颁布了gb9361-88<场地安全要求>、gb2887-89<场地技术要求>及gb50174-93(国家标准电子计算机计算中心设计规范>.     

Grey Predictive Process Control Charts

The present article intends to develop some imputation methods to reduce the impact of non response at both the occasions in two-occasion successive (rotation) sampling. Utilizing the auxiliary information, which is only available at the current occasion, estimators have been proposed for estimating the population mean at the current occasion. Estimators for the current occasion are also derived as a particular case when there is non response either on the first occasion or second occasion. Behaviors of the proposed estimators are studied and their respective optimum replacement policies are also discussed. To study the effectiveness of the suggested imputation methods, performances of the proposed estimators are compared in two different situations, with and without non response. The results obtained are demonstrated with the help of empirical studies.     

Bootstrap-Based T 2 Multivariate Control Charts

Control charts have been used effectively for years to monitor processes and detect abnormal behaviors. However, most control charts require a specific distribution to establish their control limits. The bootstrap method is a nonparametric technique that does not rely on the assumption of a parametric distribution of the observed data. Although the bootstrap technique has been used to develop univariate control charts to monitor a single process, no effort has been made to integrate the effectiveness of the bootstrap technique with multivariate control charts. In the present study, we propose a bootstrap-based multivariate T ² control chart that can efficiently monitor a process when the distribution of observed data is nonnormal or unknown. A simulation study was conducted to evaluate the performance of the proposed control chart and compare it with a traditional Hotelling's T ² control chart and the kernel density estimation (KDE)-based T ² control chart. The results showed that the proposed chart performed better than the traditional T ² control chart and performed comparably with the KDE-based T ² control chart. Furthermore, we present a case study to demonstrate the applicability of the proposed control chart to real situations.     

Using Control Charts to Corroborate Bribery in Jai Alai

Statistical process control charts were used in the State of Florida District Court to help establish the guilt of an individual who was alleged to have affected the outcome of jai alai contests by bribing some of the contestants to lose. By placing wagers on the nonbribed contestants the briber gains an increased chance of winning, which is to the detriment of the other bettors. This paper gives an example of how statistical process control techniques can be employed to detect the unusually high bets that generally accompany bribery of the contestants. If the management of the jai alai gaming facility had been using control charts on a regular basis, the game fixing might have been detected much sooner.     

Median Control Charts Based on Bootstrap Method

In this study, we propose a median control chart. In order to determine the control limits, we consider using an estimate of the variance of sample median. Also, we consider applying the bootstrap methods. Then we illustrate the proposed median control chart with an example and compare the bootstrap methods by simulation study. Finally, we discuss some peculiar features for the median control chart as concluding remarks.     

Distribution-Free Exceedance CUSUM Control Charts for Location

Distribution-free (nonparametric) control charts can be useful to the quality practitioner when the underlying distribution is not known. A Phase II nonparametric cumulative sum (CUSUM) chart based on the exceedance statistics, called the exceedance CUSUM chart, is proposed here for detecting a shift in the unknown location parameter of a continuous distribution. The exceedance statistics can be more efficient than rank-based methods when the underlying distribution is heavy-tailed and/or right-skewed, which may be the case in some applications, particularly with certain lifetime data. Moreover, exceedance statistics can save testing time and resources as they can be applied as soon as a certain order statistic of the reference sample is available. Guidelines and recommendations are provided for the chart's design parameters along with an illustrative example. The in- and out-of-control performances of the chart are studied through extensive simulations on the basis of the average run-length (ARL), the standard deviation of run-length (SDRL), the median run-length (MDRL), and some percentiles of run-length. Further, a comparison with a number of existing control charts, including the parametric CUSUM chart and a recent nonparametric CUSUM chart based on the Wilcoxon rank-sum statistic, called the rank-sum CUSUM chart, is made. It is seen that the exceedance CUSUM chart performs well in many cases and thus can be a useful alternative chart in practice. A summary and some concluding remarks are given.     

CUSUM Control Charts for Multivariate Poisson Distribution

A cumulative sum control chart for multivariate Poisson distribution (MP-CUSUM) is proposed. The MP-CUSUM chart is constructed based on log-likelihood ratios with in-control parameters, Θ₀, and shifts to be detected quickly, Θ₁. The average run length (ARL) values are obtained using a Markov Chain-based method. Numerical experiments show that the MP-CUSUM chart is effective in detecting parameter shifts in terms of ARL. The MP-CUSUM chart with smaller Θ₁ is more sensitive than that with greater Θ₁ to smaller shifts, but more insensitive to greater shifts. A comparison shows that the proposed MP-CUSUM chart outperforms an existing MP chart.     

Progressive Variance Control Charts for Monitoring Process Dispersion

In a process, the deviation from location or scale parameters affects the quality of the process and waste resources. So it is essential to monitor such processes for possible changes due to any assignable causes. Control charts are the most famous tool used to meet this intention. It is useless to monitor process location until the assurance that process dispersion is in-control. This study proposes some new two-sided memory control charts named as progressive variance (PV) control charts which are based on sample variance to monitor changes in process dispersion assuming normality of quality characteristic to be monitored. Simulation studies are made, and an example is discussed to evaluate the performance of the proposed charts. The comparison of the proposed chart is made with exponentially weighted moving average- and cumulative sum-type charts for process dispersion. The study shows that performance of the proposed charts are uniformly better than its competitors for detecting positive shifts while for detecting negative shift in the variance their performance is better for small shifts and reasonably good for moderated shifts.     

Nonparametric Shewhart-Type Sign Control Charts Based on Runs

Nonparametric control charts are considered for the median and other percentiles based on runs of sign statistics above and below the control limits. It is noted that the sign charts are advantageous in certain practical situations. Expressions for the run-length distributions are derived using Markov chain theory; several examples are given. The in-control (IC) and the out-of-control (OOC) performance of these charts are studied and compared to the existing nonparametric Wilcoxon signed-ranked charts of Chakraborti and Eryilmaz (2007 Chakraborti , S. , Eryilmaz , S. ( 2007 ). A nonparametric Shewhart-type signed-rank control chart based on runs . Commun. Statist. Simul. Computat. 36 ( 2 ): 335 – 356 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) under the normal, the double exponential and the Cauchy distributions, using the average run-length (ARL), the standard deviation of the run-length (SDRL), the false alarm rate (FAR) and some percentiles of the run-length, including the median run-length (MDRL). It is shown that the proposed “runs-rules enhanced” sign charts offer more practically desirable IC ARL (ARL ₀) and FAR values and perform better for some heavy-tailed distributions. Some concluding remarks are offered.     

EWMA Control Charts for Monitoring High Yield Processes

The main objective of this article is to scrutinize the efficiency and verify the performance superiority of the one-sided EWMA control chart on high-yield processes. The proposed control chart is designed to detect both upward and downward shifts of the fraction of non conforming products and is developed based on non transformed geometric counts. Its algorithmic function is theoretically established and numerous performance measures are extracted using analytical methods based on the Markov modeling of the chart. Comparisons with traditional high yield control charts are conducted. Optimality tables and nomograms are included to help graphical determination of the optimal chart parameters.