对我校研究生入学考试数学成绩的分析

本文利用统计的方法,使用灰色关联度对某一年的研究生入学数学成绩进行了统计分析,找出了影响考生成绩的主要因子,为我校如何改进数学教学方法及考生如何准备研究生数学入学考试提出了一些建议。     

基于圆弧样条的复杂零件型面数控测量数据拟合

讨论了数控测量数据的一般处理方法及复杂零件型面多测量点数据对数控加工的影响．研究了利用圆弧样条拟合测量数据和生成加工刀位轨迹的方法．     

期待可能性理论:引进还是拒绝

期待可能性理论是规范责任论的产物,有一定的科学性和合理性,在大陆法系中有着重要的地位和影响,焕发着巨大的生命力。但结合我国的刑法理论来分析,期待可能性理论也有其自身的局限性,具体表现为期待可能性的性质和地位无法界定,标准比较混乱,而且由于期待可能性理论和我国犯罪构成理论难以找到契合点,引进的实际意义不大,故不能将其移植到我国刑法理论中。     

Sample Size and Power Calculation in Comparing Diagnostic Accuracy of Biomarkers with Pooled Assessments

When testing of a biomarker is costly, pooling of samples becomes a useful and efficient alternative (Faraggi et al., 2003). In this paper, we develop procedures for sample size and power calculations for planning a study comparing the accuracy of biomarkers in diagnosis of diseases with pooled samples. Explicit formulas are derived for several important pooling strategies. The effects of pooling samples on sample size and power of the test are also discussed.     

西方贸易与环境理论的演化及新发展

20世纪70年代以来,贸易与环境问题就开始成为国际关注的问题,贸易自由主义者和环境保护主义者就此从未停止过争论。文章主要对其争论的主要领域进行了总结,对自由贸易和环境保护之间的关系进行了评述,希望能对我国更好地开展自由贸易提供一些借鉴。     

CCD图像的轮廓特征点提取算法

采用最大方差法将图像二值化,用图像形态学的梯度﹑细化和修剪算法来提取边缘轮廓,利用十一点曲率法得到轮廓的角点和切点的大致位置。提出了一种基于最小二乘拟合的改进算法,来进一步确定角点和切点,并对轮廓分段识别。该算法应用在基于图像处理的刀具测量系统中,实际结果表明具有良好的抗噪声性能,能准确提取出图像的特征点。     

The assessment of tumour response to treatment

Summary.  A parsimonious model for treated tumours is developed as a continuation of our previous work on regrowth curve theory. The statistical model belongs to the family of marginal non-linear models since the only linear parameters of the model are tumour specific and random facilitating parameter estimation. An important feature of the model is that it enables the estimation of the fraction of cancer cells surviving the treatment in vivo having easy-to-obtain longitudinal measurements of tumour volume. We compare several methods of estimation, including Lindstrom–Bates, iterated reweighted least squares and maximum likelihood. The last two methods are computed via the total estimating equations approach and variance least squares. The theory is illustrated with a photodynamic tumour therapy example.     

Graphical solutions for structural regression assist errors-in-variables modelling

Structural regression attempts to reveal an underlying relationship by compensating for errors in the variables. Ordinary least-squares regression has an entirely different purpose and provides a relationship between error-included variables. Structural model solutions, also known as the errors-in-variables and measurement-error solutions, use various inputs such as the error-variance ratio and x-error variance. This paper proposes that more accurate structural line gradient (coefficient) solutions will result from using the several solutions together as a system of equations. The known data scatter, as measured by the correlation coefficient, should always be used in choosing legitimate combinations of x- and y-error terms. However, this is difficult using equations. Chart solutions are presented to assist users to understand the structural regression process, to observe the correlation coefficient constraint, to assess the impact of their error estimates and, therefore, to provide better quality estimates of the structural regression gradient.     

Acceptance sampling based on truncated life tests for generalized Rayleigh distribution

This paper considers the problem of an acceptance sampling plan for a truncated life test when the lifetime follows the generalized Rayleigh distribution. For different acceptance numbers, confidence levels, and values of the ratio of the fixed experiment time to the specified mean life, the minimum sample sizes necessary to ensure the specified mean life are found. The operating characteristic values of the sampling plans and producer's risk are discussed. Some tables are presented and the use of the tables is illustrated by a numerical example.     

Objective Testing Procedures in Linear Models: Calibration of the p-values

Abstract.  An optimal Bayesian decision procedure for testing hypothesis in normal linear models based on intrinsic model posterior probabilities is considered. It is proven that these posterior probabilities are simple functions of the classical F -statistic, thus the evaluation of the procedure can be carried out analytically through the frequentist analysis of the posterior probability of the null. An asymptotic analysis proves that, under mild conditions on the design matrix, the procedure is consistent. For any testing hypothesis it is also seen that there is a one-to-one mapping – which we call calibration curve – between the posterior probability of the null hypothesis and the classical bi p -value. This curve adds substantial knowledge about the possible discrepancies between the Bayesian and the p -value measures of evidence for testing hypothesis. It permits a better understanding of the serious difficulties that are encountered in linear models for interpreting the p -values. A specific illustration of the variable selection problem is given.