Multivariate outlier detection in incomplete survey data: the epidemic algorithm and transformed rank correlations

Summary.  As a part of the EUREDIT project new methods to detect multivariate outliers in incomplete survey data have been developed. These methods are the first to work with sampling weights and to be able to cope with missing values. Two of these methods are presented here. The epidemic algorithm simulates the propagation of a disease through a population and uses extreme infection times to find outlying observations. Transformed rank correlations are robust estimates of the centre and the scatter of the data. They use a geometric transformation that is based on the rank correlation matrix. The estimates are used to define a Mahalanobis distance that reveals outliers. The two methods are applied to a small data set and to one of the evaluation data sets of the EUREDIT project.     

A-H键振动频率与原子价层轨道能

本文研究了原子价层轨道能与共价型分子氢化物中A-H键的振动频率v_(A-H)的关系,结果表明二者间有良好的线性关系,其计算式为: v_(A-H)=-a∑n_1E_1/∑n_1(A)+b (1) V_(A-H)=-c∑n_1E_1/∑n~(B)+d (2)利用上式计算的振动频率V_(A-H)值接近于文献值。从而验证了用韩长日方法计算电负性的合理性。     

NURBS曲面的算法分析及实现

讨论了ＮＵＲＢＳ曲线和节点矢量、控制点和基函数对曲面形状的影响，给出了ＮＵＲＢＳ的算法分析及其实现方案，最后，将ＮＵＲＢＳ曲面与老式曲面（如Ｂ样条、Ｂｅｚｉｅｒ曲面等）进行了比较。     

Improved Monte Carlo inference for models with additive error

Some statistical models defined in terms of a generating stochastic mechanism have intractable distribution theory, which renders parameter estimation difficult. However, a Monte Carlo estimate of the log-likelihood surface for such a model can be obtained via computation of nonparametric density estimates from simulated realizations of the model. Unfortunately, the bias inherent in density estimation can cause bias in the resulting log-likelihood estimate that alters the location of its maximizer. In this paper a methodology for radically reducing this bias is developed for models with an additive error component. An illustrative example involving a stochastic model of molecular fragmentation and measurement is given.     

基于模糊判断矩阵信息确定专家权重的方法

本文对群组模糊判断矩阵集结过程中确定专家权重的问题进行了研究,建立了模糊判断矩阵的特征矩阵和求解群集结矩阵的最优化模型,通过矩阵之间距离度量判断信息自身逻辑一致性程度和群体相容性程度,给出一种基于专家判断信息的可信度计算其后验权重的方法,最后用算例予以说明.     

基于熵权法的科学技术评价模型及其实证研究

以“坚持以人为本,全面、协调、可持续”的科学发展观内涵为指导思想,通过科技指标的海选、筛选和理性分析构建了科技综合评价指标体系。用熵权法客观地对评价指标进行赋权,建立了基于熵权法的中国“十五”期间的科学技术发展状况评价模型,并给出了“十一五”期间科技发展政策建议。研究特色有五：①根据国际关注、又好又快、可持续发展和以人为本的原则建立指标体系,使科学技术的评价反映科学发展观的要求;②通过熵权法客观地确定指标权重,避免了人为主观确定权重的随意性;③利用熵权法确定的熵值,确保了仅用24个指标反映了95．5％以上的原始信息;④通过对影响科学技术整体效果的准则层进行评价,有助于找出科技发展各环节存在的问题;⑤通过对中国“十五”期间科技发展中的主要问题的分析,给出了“十一五”期间中国科技发展的政策建议。     

DNA芯片技术

DNA芯片可用于核酸序列的测定及基因突变检测等,这里对DNA芯片的制作、作用原理、性能及用途等进行了综述。     

局部均衡函数及其构造

研究了局部均衡函数,定义了改进的局部变权向量,提出了与之对应的状态局部变权向量和局部均衡函数,证明了两类函数是局部均衡函数;利用局部变权向量建立了企业信用评估模型,并通过实例说明了该理论是有效的和合理的.     

A Proportional Hazards Regression Model for the Subdistribution with Covariates‐adjusted Censoring Weight for Competing Risks Data

With competing risks data, one often needs to assess the treatment and covariate effects on the cumulative incidence function. Fine and Gray proposed a proportional hazards regression model for the subdistribution of a competing risk with the assumption that the censoring distribution and the covariates are independent. Covariate‐dependent censoring sometimes occurs in medical studies. In this paper, we study the proportional hazards regression model for the subdistribution of a competing risk with proper adjustments for covariate‐dependent censoring. We consider a covariate‐adjusted weight function by fitting the Cox model for the censoring distribution and using the predictive probability for each individual. Our simulation study shows that the covariate‐adjusted weight estimator is basically unbiased when the censoring time depends on the covariates, and the covariate‐adjusted weight approach works well for the variance estimator as well. We illustrate our methods with bone marrow transplant data from the Center for International Blood and Marrow Transplant Research. Here, cancer relapse and death in complete remission are two competing risks.