试析巴以冲突的经济内涵——从以色列对巴勒斯坦经济的全面控制谈起

在2000年9月爆发的巴以冲突中,以色列不仅对巴勒斯坦实行领土占领,而且为保证自身的绝对安全,对巴勒斯坦采取了经济上的全面控制,双方的经济差距由此越来越大,这种差距不仅仅是巴以冲突的结果,更是引发双方冲突的导火线和原因.     

项目教学法在“数控加工工艺与编程”课程中的应用

介绍了项目教学法在"数控加工工艺与编程"课程中项目的设定以及项目的教学组织和实施过程。通过实例阐述了项目教学法的应用方法,通过项目教学法不仅提高了学生的动手操作能力和创新能力;也进一步培养学生的自主学习能力,提高学生的学习兴趣。     

债权融资下的控制权安排

在控制权具有私人收益的情况下,它对于企业家具有激励作用;同时,由于存在道德风险,债权人可以运用控制权来保障自己的回报,因此,控制权对于债权人又具有承兑作用,这两种作用相互冲突,必然会对债务融资控制权的安排带来影响。债务融资下,最佳的控制权安排取决于控制权两种作用之间的权衡,并非人们通常认为的债务越多,控制权交给债权人的比例就越高     

Multivariate Process Variability Monitoring

Understanding multivariate variability is a difficult task because there is no single measure that can be properly used. This article presents a new measure that features good properties. If this measure is simultaneously used with generalized variance, it will give a better understanding of multivariate variability. It can also efficiently be used for large data sets with high dimensions. Furthermore, when it is used for constructing a Shewhart-type chart to monitor multivariate variability, the resulting chart has a much better out-of-control ARL than the generalized variance chart. An example illustrates its advantage.     

Constructions of Residual Treatment Effects Designs for Comparing Test Treatments with a Control

This article deals with residual treatment effects designs for the purpose of comparing v test treatments with a control treatment when the number of periods is no larger than v + 1. Control balanced residual treatment effects designs, which are Schur-optimal, are considered. Some methods of their construction are given.     

An adaptive multivariate CUSUM control chart for signaling a range of location shifts

ABSTRACT

In this work, we proposed an adaptive multivariate cumulative sum (CUSUM) statistical process control chart for signaling a range of location shifts. This method was based on the multivariate CUSUM control chart proposed by Pignatiello and Runger (1990 Pignatiello, J.J., Runger, G.C. (1990). Comparisons of multivariate CUSUM charts. J. Qual. Technol. 22(3):173–186.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]), but we adopted the adaptive approach similar to that discussed by Dai et al. (2011 Dai, Y., Luo, Y., Li, Z., Wang, Z. (2011). A new adaptive CUSUM control chart for detecting the multivariate process mean. Qual. Reliab. Eng. Int. 27(7):877–884.[Crossref], [Web of Science ®] , [Google Scholar]), which was based on a different CUSUM method introduced by Crosier (1988 Crosier, R.B. (1988). Multivariate generalizations of cumulative sum quality-control schemes. Technometrics 30(3):291–303.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]). The reference value in this proposed procedure was changed adaptively in each run, with the current mean shift estimated by exponentially weighted moving average (EWMA) statistic. By specifying the minimal magnitude of the mean shift, our proposed control chart achieved a good overall performance for detecting a range of shifts rather than a single value. We compared our adaptive multivariate CUSUM method with that of Dai et al. (2001 Dai, Y., Luo, Y., Li, Z., Wang, Z. (2011). A new adaptive CUSUM control chart for detecting the multivariate process mean. Qual. Reliab. Eng. Int. 27(7):877–884.[Crossref], [Web of Science ®] , [Google Scholar]) and the non adaptive versions of these two methods, by evaluating both the steady state and zero state average run length (ARL) values. The detection efficiency of our method showed improvements over the comparative methods when the location shift is unknown but falls within an expected range.     

Large sample tests for equality of medians under unequal right-censoring

Two tests are proposed for testing equality of the medians of two distributions on the basis of right cansored data. The tests do not require any assumption on the scales or the shapes of the distributions and can be used without assuming equal censorship in the two samples. Under the sequence of translation alternatives the proposed tests are equally efficient when the distributions belong to the same location and scale family. Some indications are provided about the significance levels of the tests based on simulation results.     

Evaluation of control charts under linear trend

The performance of several control charting schemes is studied when the process mean changes as a linear trend. The control charts considered include the Shewhart chart, the Shewhart chart supplemented with runs rules, the cumulative sum (CUSUM) chart, the exponentially weighted moving average (EWMA) chart, and a generalized control chart.     

Calibrated path sampling and stepwise bridge sampling

A computational problem in many fields is to evaluate multiple integrals and expectations simultaneously. Consider probability distributions with unnormalized density functions indexed by parameters on a 2-dimensional grid, and assume that samples are simulated from distributions on a subgrid. Examples of such unnormalized density functions include the observed-data likelihoods in the presence of missing data and the prior times the likelihood in Bayesian inference. There are various methods using a single sample only or multiple samples jointly to compute each integral. Path sampling seems a compromise, using samples along a 1-dimensional path to compute each integral. However, different choices of the path lead to different estimators, which should ideally be identical. We propose calibrated estimators by the method of control variates to exploit such constraints for variance reduction. We also propose biquadratic interpolation to approximate integrals with parameters outside the subgrid, consistently with the calibrated estimators on the subgrid. These methods can be extended to compute differences of expectations through an auxiliary identity for path sampling. Furthermore, we develop stepwise bridge-sampling methods in parallel but complementary to path sampling. In three simulation studies, the proposed methods lead to substantially reduced mean squared errors compared with existing methods.     

On control charts for monitoring the variance of a time series

In this paper we derive control charts for the variance of a Gaussian process using the likelihood ratio approach, the generalized likelihood ratio approach, the sequential probability ratio method and a generalized sequential probability ratio procedure, the Shiryaev–Roberts procedure and a generalized modified Shiryaev–Roberts approach. Recursive presentations for the calculation of the control statistics are given for autoregressive processes of order 1. In an extensive simulation study these schemes are compared with existing control charts for the variance. In order to asses the performance of the schemes both the average run length and the average delay are used.