新时期高校以德治校的理性思考

高校作为“以德化育”的主要载体,肩负着为未来社会发展培养接班人的历史使命。在新的历史条件下,高校应认真贯彻“以德治国”之方略,切实做到以德治校。     

中国上市公司股利政策探讨--从代理成本理论的角度视之

中国上市公司的股利政策与其他国家相比,表现出许多独特之处,形成了"中国股利之谜".在国外,股利政策是控制代理成本的一种工具,在中国,现行股利政策恰好是代理问题没有得到解决的产物,代理成本过高是导致股利政策非理性的重要原因.应当从减持国有股、完善上市公司的股权结构等措施入手,促进股利分配政策的理性决策.在此基础上,进一步发挥股利政策降低代理成本的作用.     

公司治理结构中的代理成本与审计独立性的相关性研究

本文从"提高审计独立性对代理成本的影响"和"代理成本的高低对审计独立性的影响"两个角度,对代理成本与审计独立性的相关性进行了理论分析,认为代理成本与审计独立性具有正相关性,并将这一结论作为研究假设,提出了建立数学模型对两者的相关性进行实证研究的思路。文章认为,要提高审计独立性将会导致公司代理成本的相应提高,反之,代理成本越高,被审单位从其自身利益出发,必然要提高审计独立性。     

公私合营（PPP）项目的规制研究

恰当的规制是公私合营制（PPP）项目健康发展的重要保证,同时如何对PPP项目进行恰当规制也是学术界研究的热点问题.文章采用文本分析方法,对PPP项目规制的内涵、目标以及规制体系的研究成果进行了综合分析.结果表明,目前宏观层面上的研究较少,一些学者只是提出了规制体系建立的思路与原则,大部分研究则集中在规制体系的微观层面即规制实施主体及规制工具等方面.动态的价格规制研究、规制体系中各要素间的关系研究及规制的可信性问题的研究是PPP项目规制未来的研究方向.     

Monitoring Nonlinear Profiles with Random Effects by Nonparametric Regression

The monitoring of process/product profiles is presently a growing and promising area of research in statistical process control. This study is aimed at developing monitoring schemes for nonlinear profiles with random effects. We utilize the technique of principal components analysis to analyze the covariance structure of the profiles and propose monitoring schemes based on principal component (PC) scores. The number of the PC scores used in constructing control charts is crucial to the detecting power. In the Phase I analysis of historical data, due to the dependency of the PC-scores, we adopt the usual Hotelling T ² chart to check the stability. For Phase II monitoring, we study individual PC-score control charts, a combined chart scheme that combines all the PC-score charts, and a T ² chart. Although an individual PC-score chart may be perfect for monitoring a particular mode of variation, a chart that can detect general shifts, such as the T ² chart and the combined chart scheme, is more feasible in practice. The performances of the schemes under study are evaluated in terms of the average run length.     

A Multivariate Adaptive Exponentially Weighted Moving Average Control Chart

A multivariate extension of the adaptive exponentially weighted moving average (AEWMA) control chart is proposed. The new multivariate scheme can detect small and large shifts in the process mean vector effectively. The proposed scheme can be viewed as a smooth combination of a multivariate exponentially weighted moving average (MEWMA) chart and a Shewhart χ²-chart. The optimal design of the proposed chart is given according to a pre-specified in-control average run length and two shift sizes; a small and large shift each measured in terms of the non centrality parameter. The signal resistance of the newly proposed multivariate chart is also given. Comparisons among the new chart, the MEWMA chart, and the combined Shewhart-MEWMA (S-MEWMA) chart in terms of the standard and worst-case average run length profiles are presented. In addition, the three charts are compared with respect to their worst-case signal resistance values. The proposed chart gives somewhat better worst-case ARL and signal resistance values than the competing charts. It also gives better standard ARL performance especially for moderate and large shifts. The effectiveness of our proposed chart is illustrated through an example with simulated data set.     

A Distribution-Free Control Chart Based on Order Statistics

In this article, we introduce a new distribution-free Shewhart-type control chart that takes into account the location of a single order statistic of the test sample (such as the median) as well as the number of observations in that test sample that lie between the control limits. Exact formulae for the alarm rate, the run length distribution, and the average run length (ARL) are all derived. A key advantage of the chart is that, due to its nonparametric nature, the false alarm rate and in-control run length distribution are the same for all continuous process distributions, and so will be naturally robust. Tables are provided for the implementation of the chart for some typical ARL values and false alarm rates. The empirical study carried out reveals that the new chart is preferable from a robustness point of view in comparison to a classical Shewhart-type chart and also the nonparametric chart of Chakraborti et al. (2004 Chakraborti , S. , van der Laan , P. , van de Wiel , M. A. ( 2004 ). A class of distribution-free control charts . J. Roy. Statist. Soc. Ser. C-Appl. Statist. 53 ( 3 ): 443 – 462 .[Web of Science ®] , [Google Scholar]).     

A New Control Scheme Always Better Than X-Bar Chart

A new control scheme is proposed by borrowing the idea of the Benjamini–Hochberg procedure for controlling the false discovery rate in multiple testing. It is shown theoretically that the proposed 2-span control scheme outperforms the Shewhart X-bar chart in terms of the average run length under any size of mean shifts. Some simulations are carried out to demonstrate that the proposed scheme having various span sizes always outperforms the X-bar chart in terms of the average run lengths.     

A Nonparametric Synthetic Control Chart Using Sign Statistic

This article presents a synthetic control chart for detection of shifts in the process median. The synthetic chart is a combination of sign chart and conforming run-length chart. The performance evaluation of the proposed chart indicates that the synthetic chart has a higher power of detecting shifts in process median than the Shewhart charts based on sign statistic as well as the classical Shewhart X-bar chart for various symmetric distributions. The improvement is significant for shifts of moderate to large shifts in the median. The robustness studies of the proposed synthetic control chart against outliers indicate that the proposed synthetic control chart is robust against contamination by outliers.