Semi-empirical likelihood confidence intervals for the differences of quantiles with missing data

Detecting population （group） differences is useful in many applications, such as medical research. In this paper, we explore the probabilistic theory for identifying the quantile differences .between two populations. Suppose that there are two populations x and y with missing data on both of them, where x is nonparametric and y is parametric. We are interested in constructing confidence intervals on the quantile differences of x and y. Random hot deck imputation is used to fill in missing data. Semi-empirical likelihood confidence intervals on the differences are constructed.     

艾拉姆咖(Эрланга)分布小样本区间估计和检验问题研究

本文研究了艾拉姆咖分布的小样本区间估计和检验问题.给出了检验统计量和相应的拒绝域.比较了指数分布和艾分布的区别和差异.指出在对装备维修工时的估计时,运用艾分布可能更加精确和有意义;并运用实例分析了区间估计精度.文章对装备维修工时的估计具有一定意义.     

不完备信息下的灰色粗糙集成决策模型侯亚林

In this paper, for multiple attribute decision-making problem in which attribute values are interval grey numbers and some of them are null values, a decision model based on grey rough sets integration with incomplete information is proposed. We put forward incidence degree coefficient formula for grey interval, by information entropy theory and analysis technique, the method and principle is presented to fill up null values. We also establish the method of grey interval incidence cluster. Because grey system theory and Rough set theory are complementary each other, decision table with preference information is obtained by the result of grey incidence cluster. An algorithm for inducing decision rules based on rough set theory and the dominance relationship is presented. In some extent, this algorithm can deal with decision-making problem in which the attribute values are interval grey numbers and some of them are null values. Contrasted with classical model of cluster decision-making, the algorithm has an advantage of flexibility and compatibility to new information.     

随机右截尾情形下两个指数分布总体的比较

研究了随机右截尾情形下两个指数分布的参数估计.在两个指数分布的刻度参数都未知时,得到了两个指数分布的刻度参数的最大似然估计与参数比的区间估计.     

随机设计非线性混合模型的统计分析

本文研究了个体观察次数为随机的非线性 混合效应模型中参数的点估计以及区间估计. 在仅给出适当的矩条件下, 给出了固定效应、随机效应的方差阵以及误差方差的矩估计, 并证明了估计量的相合性及渐近正态性. 为给出误差方差以及随机效应方差分量的置信区间, 本文也给出了误差及随机效应的四阶矩估计. 随机模拟说明了方法的有效性.     

基于相对熵的不完全信息群体专家权重的集结

针对属性权重信息和属性效用信息都不完全的群体多属性决策问题,运用相对熵理论提出了一种专家权重的确定方法．该方法通过集结各方案的综合评价值向量,客观地得到专家的权重,避免系统聚类方法中由给定相似度水平归类而产生的主观性问题．应用实例表明了方法的有效性和实用性．     

n维球内均匀分布的参数估计

研究了n维球内均匀分布的参数的点估计与区间估计,利用次序统计量得到了球半径的最大似然估计,在此基础上构造了球半径的无偏估计,并且证明了该无偏估计的相合性.利用构造枢轴量的方法得到了球半径的最短置信区间.     

哒螨灵在苹果和土壤上残留以及降解行为研究

本研究建立了基于高效液相色谱为基础的哒螨灵分析方法,并对哒螨灵在安徽淮北和陕西咸阳两地苹果上的消解和残留行为进行了研究,同时还考察了哒螨灵在两地土壤中的降解和残留行为．哒螨灵在苹果中的消解动态方程：陕西咸阳为C=0．4007e^-0.1535t,半衰期T1/2=4．5天;安徽淮北=0．1096e^-0.1464t,半衰期T1/2=4．7天;在土壤中的消解动态方程：陕西咸阳为C=0．7978e^0.1218t,半衰期T1/2=5．7天;安徽淮北C=1．4024e^-0.0912t,半衰期T1/2=7．6天．在推荐使用高剂量和推荐高剂量1．5倍情况下,施药1-2次,末次药后7天,哒螨灵在苹果中的残留为0．02～0．14mg／kg;药后14天为0．01—0．12mg／kg．试验结果表明,药后7天,苹果中哒螨灵的残留量低于2mg／kg,用药次数1-2次,每次间隔7天的情况下,在苹果上的安全间隔期可定为7天．     

Variable sampling interval Shewhart control charts for monitoring the multivariate coefficient of variation

In many industrial manufacturing processes, the ratio of the variance to the mean of a quantity of interest is an important characteristic to ensure the quality of the processes. This ratio is called the coefficient of variation (CV). A lot of control charts have been designed for monitoring the CV of univariate quantity in the literature. However, the CV control charts for multivariate quantity have not received much attention yet. In this paper, we investigate a variable sampling interval (VSI) Shewhart control chart for monitoring multivariate CV. The time between two consecutive samples is allowed to vary according to the previous value of the multivariate CV, which will help the chart to detect the process shifts faster. The comparison with the fixed sampling interval Shewhart chart is implemented to highlight the advantage of the VSI method. Finally, an illustrative example is demonstrated on real data.     

A characterization of cycle-free unit probe interval graphs

A graph is a probe interval graph (PIG) if its vertices can be partitioned into probes and nonprobes with an interval assigned to each vertex so that vertices are adjacent if and only if their corresponding intervals overlap and at least one of them is a probe. PIGs are a generalization of interval graphs introduced by Zhang for an application concerning the physical mapping of DNA in the human genome project. PIGs have been characterized in the cycle-free case by Sheng, and other miscellaneous results are given by McMorris, Wang, and Zhang. Johnson and Spinrad give a polynomial time recognition algorithm for when the partition of vertices into probes and nonprobes is given. The complexity for the general recognition problem is not known. Here, we restrict attention to the case where all intervals have the same length, that is, we study the unit probe interval graphs and characterize the cycle-free graphs that are unit probe interval graphs via a list of forbidden induced subgraphs.