Aspects of Dependence in Cuadras–Auge Family

In this article, we study the dependence structure of Cuadras–Auge (C–A) family of bivariate distributions. We also obtain some association measures and two local dependence functions for this family. In addition, we compare expectation of local dependence function and Pearson's rho via numerical study.     

大学生课余生活现状与引导对策

大学生的课余生活是高等教育中不可疏忽的教育主题。调查显示，目前大学生的课余生活存在一些比较突出的问题。引导学生课余生活的安排，提高大学生课余生活的质量，应从重视其非智力因素的培养、加强校园文化建设、培养良好的人格品质、鼓励大学生投身于社会实践，提高大学生的就业能力等多途径入手。     

广东工业大学大学英语课程改革中的问题研究

文章介绍了广东工业大学根据教育部<大学英语课程教学要求(试行)>精神,开展新一轮大学英语课程改革的情况,对大学英语课程改革中存在的问题进行了分析,并提出了若干解决措施.     

高校学生档案管理现状与对策思考

高校学生档案管理普遍存在管理模式多、缺标准、无规范、管理方式落后等问题，加强《高校档案管理办法》执行力度，加强学生档案规范化管理和信息网络化建设是改进和完善高校学生档案管理的必要措施。     

Clustering Microarray Data: Theoretical and Practical Issues

The analysis of microarray data is a widespread functional genomics approach that allows for the monitoring of the expression of thousands of genes at once. The analysis of the great amount of data generated in a microarray experiment requires powerful statistical techniques. One of the first tasks of the analysis of microarray data is to cluster data into biologically meaningful groups according to their expression patterns. In this article, we discuss classical as well as recent clustering techniques for microarray data. We pay particular attention to both theoretical and practical issues and give some general indications that might be useful to practitioners.     

GSH Dependence Modeling with an Application to Risk Management

The generalized secant hyperbolic distribution (GSH) can be used to represent financial data with heavy tails as an alternative to the Student-t, because it guarantees the existence of all moments, also with a high kurtosis value. In order to obtain a multivariate extension of the GSH distribution, in this article we present two approaches to model the dependence, the copula approach and independent component analysis. Since the methodologies considered allow to simulate the GSH dependence, we show also the empirical results obtained in the estimation of risk of a financial portfolio by the Monte Carlo method.     

A monte carlo study of the friedman and conover tests in the single-factor repeated measures design

A Monte Carlo study was used to compare the Type I error rates and power of two nonparametric tests against the F test for the single-factor repeated measures model. The performance of the nonparametric Friedman and Conover tests was investigated for different distributions, numbers of blocks and numbers of repeated measures. The results indicated that the type of the distribution has little effect on the ability of the Friedman and Conover tests to control Type error rates. For power, the Friedman and Conover tests tended to agree in rejecting the same false hyporhesis when the design consisted of three repeated measures. However, the Conover test was more powerful than the Friedman test when the number of repeated measures was 4 or 5. Still, the F test is recommended for the single-factor repeated measures model because of its robustness to non-normality and its good power across a range of conditions.     

Selecting all treatments better than a control using existing tables

In this paper subset selection procedures for selecting all treatment populations with means larger than a control population are proposed. The treatments and control are assumed to have a multivariate normal distribution. Various covariance structures are considered. All of the proposed procedures are easily implemented using existing tables of the multivariate normal and multivariate t distributions. Some other procedures which have been proposed require extensive and unavailable tables for their implementation