调查表可重复性信度研究方法

本文结合安庆市１９９２年部分乡镇卫技人员二次心态调查资料，介绍了一种调查表内计量测量的条目的可重复性信度分析方法──方差分析法，以及定性测量的条目两次调查结果一致度分析方法，对影响调查表可重复性的主要因素进行了讨论，强调了调查表信度分析的意义这对于我们在大型现场研究中提高调查表设计能力，提高测量的效度与精度有重要理论指导意义．     

有理插值的基本特征

１　引　言 记 ｎ为次数不超过ｎ的一元多项式函数类,约定零多项式的次数为－∞,即ｄｅｅ（０）＝－∞;记 ｍ,ｎ为分子属于 ｍ,分母属于 ｎ＼｛０｝的一元有理函数类．我们约定：本文所采用的概念和记号将与文［１］保持一致,本文中“有理插值问题”系指文［１］中“有理插值问题（２．１）（２．２）”,并简记为ＲＩＰ． 文［１］在［２－８］的基础上引进了ＲＩＰ的　方程组,定义了　插值式,指出了其与经典结果的关系,这为我们分析ＲＩＰ提供了一个有力的工具．本文将在文［１］的基础上,深入讨论ＲＩＰ的基本特征．在本节和下…     

L－fuzzy集网的R－收敛性质

本文在ＬＦ拓扑空间中建立了Ｌ－ｆｕｚｚｙ集网的弱收敛（Ｒ－收敛）概念，应用文［４］中的Ｒ－闭包，系统讨论了它们的性质，证明了等式ＲｌｉｍＡ＿ｎ＝∧（∨Ａ＿ｍ）＿Ｒ和ＲｌｉｍＡ＿ｎ＝Ａ＿ｎ＝∧（∨Ａ＿ｍ）＿Ｒ并且给出了Ｌ－ｆｕｚｚｙ集网与其子网之间的关系。     

重复测量中两组均值是否相等的假设检验

在重复测量中，存在着检验两个随机试验组的各次测量均值是否相等的问题。假定所有试验对象初始值无差异，那么只需对所有均值的对比进行检验就可以了；若这个假定不成立，则需要直接检验各次测量的均值是否均对应相等。在正态性、复合对称的假定下，前一种情形已有很好的结论。针对后面一种情况，本文采用似然比检验的方法进行了检验，构造出了检验统计量的分布函数表。并对计算的精确度作了较好的控制。     

具有测量误差的非线性模型的Bayes估计

测量中大量的函数模型都是非线性回归模型．当回归变量含有一定的测量误差时，我们得到非线性测量误差模型．本讨论了这种模型中未知参数具有正态先验分布时的参数Bayes估计方法，并对这种估计进行了影响分析，证明了删除模型与均值漂移模型中参数的Bayes估计相同，利用Cook统计量给出了删除模型下参数的Bayes估计的影响度量．     

关于阶数为奇数的布尔矩阵行空间的基数

设Ｂｎ表示所有的ｎ阶布尔矩阵的集合，Ｒ（Ａ）表示Ａ∈Ｂｎ的行空间，｜Ｒ（Ａ）｜表示Ｒ（Ａ）的基数．设ｍ，ｎ为正整数，本文证明了（Ⅰ）ｍ∈［１，４６］，［１，７８］，分别存在Ａ∈Ｂ７，Ａ∈Ｂ８，使得｜Ｒ（Ａ）｜＝ｍ．（Ⅱ）当ｎ≥９为奇数时，则ｍ∈［１，２（ｎ＋３）／２＋２（ｎ＋１）／２＋…＋２３］，存在Ａ∈Ｂｎ，使得｜Ｒ（Ａ）｜＝ｍ．     

基于矩形自卷积窗算法数据测量的充电桩设计

为有效抑制太阳能供电充电桩由于外界环境的温度和光照强度的不规律变化造成光伏电池输出电压的发生扰动,进而引起充电桩输入电能发生畸变,导致数据采样与信号周期不同步产生的测量误差,在说明准同步采样原理的基础上,进行了太阳能供电充电桩的硬件和软件设计,通过充电实验验证了系统功能的完整性和稳定性.并利用矩形自卷积窗作为加窗方法,实现了对充电桩电量数据的测量.测量结果表明,方法可以将因采样不同步所引起的测量误差控制在较好的范围内,并对有功功率、电压有效值和电流有效值的测量误差进行了分析.     

基于控制图的马田系统马氏空间生成机理研究

马田系统是以马氏距离为测量尺度,通过选取正常样本构建马氏空间,对多元系统进行诊断和预测的分类技术。马氏距离对样本数据的变化非常敏感,因此用于构建马氏空间的正常样本的数据质量直接影响到分类的准确率。实际应用中正常样本的选取大多依据主观经验判断,缺乏客观规范的选择机制。本文提出基于控制图的马氏空间生成机理,先由专家选取的正常样本构建初始马氏空间,再以每个正常样品在初始马氏空间和对应的缩减马氏空间上的马氏距离增量作为新的测量尺度,以此建立单值控制图,利用控制图稳定性判定规则剔除异常数据,从而得到稳定状态的马氏空间。实验分析结果表明该方法的有效性且提高了马田系统分类的准确率。     

Schur型分块Hermitian矩阵控制定理

本文通过对序列集合Γｍ的由对称群Ｓｍ的子群Ｇ及Ｇ的不可约特征标λ诱导的特殊子集△的恰当分划，实现了Ｒ．Ｍｅｒｒｉｓ所提出的分块Ｈｅｒｍｉｔｉａｎ矩阵控制定理从初等对称函数型到Ｓｃｈｕｒ函数型的推广，并对不同群诱导的Ｓｃｈｕｒ型广义矩阵函数之间的关系作了讨论．     

测量误差对单位根检验的影响

本文推导了加性平稳测量误差下单位根检验中有截距和无截距情形下T(p-1)与τ两种统计量的极限分布。理论分析和蒙特卡罗实验均表明,单位根检验结果易受到测量误差的影响。测量误差将导致统计量分布向左偏移,从而导致检验水平的扭曲和检验功效的增加。左偏程度受测量误差方差及其一阶协方差的相对大小控制,而与测量误差的均值大小和概率分布无关。测量误差方差增大,左偏更严重;正的一阶协方差可以减少和抵消统计量分布的向左偏离,而负的一阶协方差将加剧左偏的程度;一阶协方差接近于方差时,左偏程度很小。测量误差的方差相对较小时,其对单位根检验的影响可以忽略。     

Penalized sample average approximation methods for stochastic programs in economic and secure dispatch of a power system

In this paper, we develop a stochastic programming model for economic dispatch of a power system with operational reliability and risk control constraints. By defining a severity-index function, we propose to use conditional value-at-risk (CVaR) for measuring the reliability and risk control of the system. The economic dispatch is subsequently formulated as a stochastic program with CVaR constraint. To solve the stochastic optimization model, we propose a penalized sample average approximation (SAA) scheme which incorporates specific features of smoothing technique and level function method. Under some moderate conditions, we demonstrate that with probability approaching to 1 at an exponential rate with the increase of sample size, the optimal solution of the smoothing SAA problem converges to its true counterpart. Numerical tests have been carried out for a standard IEEE-30 DC power system.     

Economic design of an adaptive <Emphasis Type="Italic">T</Emphasis><Superscript>2</Superscript> control chart

Varying three parameters of the Hotelling's T² control chart, namely, the sample size, the sampling interval length, and the action limit, results in a great improvement over the traditional T² control chart particularly for the small process shift. This paper presents the economic model for designing the variable parameters T² chart. In the economic design, a cost function is constructed, involving the cost of sampling and testing, the cost of false alarm, the cost to detect and remove the assignable cause, and the cost when the process is operating out-of-control. Also, a heuristic method of finding optimal values of adaptive design parameters for minimizing the cost function is presented. Variable and fixed parameters T² control charts are compared with respect to the expected loss per unit time. Furthermore, the effects of the initial sample number (used for estimating the parameters of F-distribution) upon the operating cost and adaptive design parameters are examined.     

Covariate Selection in High-Dimensional Generalized Linear Models With Measurement Error

In many problems involving generalized linear models, the covariates are subject to measurement error. When the number of covariates p exceeds the sample size n, regularized methods like the lasso or Dantzig selector are required. Several recent papers have studied methods which correct for measurement error in the lasso or Dantzig selector for linear models in the p > n setting. We study a correction for generalized linear models, based on Rosenbaum and Tsybakov’s matrix uncertainty selector. By not requiring an estimate of the measurement error covariance matrix, this generalized matrix uncertainty selector has a great practical advantage in problems involving high-dimensional data. We further derive an alternative method based on the lasso, and develop efficient algorithms for both methods. In our simulation studies of logistic and Poisson regression with measurement error, the proposed methods outperform the standard lasso and Dantzig selector with respect to covariate selection, by reducing the number of false positives considerably. We also consider classification of patients on the basis of gene expression data with noisy measurements. Supplementary materials for this article are available online.     

Joint economic design of EWMA control charts for mean and variance

Control charts with exponentially weighted moving average (EWMA) statistics (mean and variance) are used to jointly monitor the mean and variance of a process. An EWMA cost minimization model is presented to design the joint control scheme based on pure economic or both economic and statistical performance criteria. The pure economic model is extended to the economic-statistical design by adding constraints associated with in-control and out-of-control average run lengths. The quality related production costs are calculated using Taguchi’s quadratic loss function. The optimal values of smoothing constants, sampling interval, sample size, and control chart limits are determined by using a numerical search method. The average run length of the control scheme is computed by using the Markov chain approach. Computational study indicates that optimal sample sizes decrease as the magnitudes of shifts in mean and/or variance increase, and higher values of quality loss coefficient lead to shorter sampling intervals. The sensitivity analysis results regarding the effects of various inputs on the chart parameters provide useful guidelines for designing an EWMA-based process control scheme when there exists an assignable cause generating concurrent changes in process mean and variance.     

含测量误差的部分线性模型的发散参数估计(英文)

本文考虑了部分线性模型中,线性部分协变量含有测量误差,并且线性部分的参数随着样本量的增大而发散的估计问题.我们考虑了用可观测的替代变量来替代不可观察到的真实变量,这种替代变量的期望与真实变量存在线性关系.我们提出了估计方法,并研究了估计量的相合性与渐进正态性.此外,我们研究了发散参数的发散速度.我们通过模拟来说明该估计的实际效果.     

Empirical Likelihood Inference Under Stratified Random Sampling in the Presence of Measurement Error

Suppose that several different imperfect instruments and one perfect instrument are used independently to measure some characteristic of a population. In order to make full use of the sample information, in this paper the empirical likelihood method is put forward for making inferences on parameters of interest under stratified random sampling in the presence of measurement error, Our results show that it can lead to estimators which are asymptotically normal and utilize all the available sample information. We also obtain the asymptotic distribution of empirical likelihood testing statistics. In particular, we apply the method to obtain estimator and confidence interval of population mean.     

基于联系数的钢筋抗拉强度测量不确定度评定新方法

钢筋抗拉强度的不确定度包括:钢筋直径的不确定度分量,拉力的不确定度分量,检测结果重复性引入的不确定度分量,数据修约的不确定度分量等等,因此,测量不确定度是与测量数据相联系的,联系数是处理不确定性问题的一种系统数学理论,可以用联系数来表示测量不确定度,为此,提出一种基于联系数的钢筋抗拉强度测量不确定度评定的新方法.     

Economic design of attribute np control charts using a variable sampling policy

To use a control chart, the quality engineer should specify three decision variables, namely the sample size, the sampling interval and the critical region of the chart. A significant part of recent research relaxed the constraint of using fixed design parameters to open the way to a new type of control charts called adaptive ones where at least one of the decision variables may change in real time based on the last data information. These adaptive schemes have proven their effectiveness from economical and statistical point of views. In this paper, the economic design of an attribute np control chart using a variable sampling interval (VSI) is treated. A sensitivity analysis is conducted to search for optimal design parameters minimizing the expected total cost per hour and to reveal the impact of the process and cost parameters on the behavior of optimal solutions. An economic comparison between the classical np chart, variable sample size (VSS) np control chart and VSI chart is conducted. It is found that switching from the classical attribute chart to the VSI sampling strategy results in notable cost savings and in reduction of the average time to signal and the average number of false alarms. In most cases of the sensitivity analysis, the VSI np chart outperforms the VSS np chart based on economical and statistical considerations. Copyright © 2014 John Wiley & Sons, Ltd.     

Trade-off between sample size and accuracy: Case of measurements under interval uncertainty

In many practical situations, we are not satisfied with the accuracy of the existing measurements. There are two possible ways to improve the measurement accuracy:

• First, instead of a single measurement, we can make repeated measurements; the additional information coming from these additional measurements can improve the accuracy of the result of this series of measurements.

• Second, we can replace the current measuring instrument with a more accurate one; correspondingly, we can use a more accurate (and more expensive) measurement procedure provided by a measuring lab – e.g., a procedure that includes the use of a higher quality reagent.

In general, we can combine these two ways, and make repeated measurements with a more accurate measuring instrument. What is the appropriate trade-off between sample size and accuracy? This is the general problem that we address in this paper.     

Average performance of adaptive algorithms for programming co‐ordinate measuring machines under budget constraint

In this paper we develop two adaptive algorithms for programming co‐ordinate measuring machines assuming fixed sampling budget. Two different costs are considered: the travelling cost of the machine probe, and the sampling cost to read and store all measurements. Simulation is used to compare the average performance of the proposed algorithms under the assumption of Wiener measure on the space of all surface contours of the manufactured parts. Expected value of the probability of Type II error is the criterion that we use to characterize algorithms performance. Analysis shows that placing sample points according to the criterion of maximizing the expected gain demonstrates a substantial improvement in the average performance. Copyright © 1999 John Wiley & Sons, Ltd.