A course in constructing effective displays of data for pharmaceutical research personnel

Interpreting data and communicating effectively through graphs and tables are requisite skills for statisticians and non‐statisticians in the pharmaceutical industry. However, the quality of visual displays of data in the medical and pharmaceutical literature and at scientific conferences is severely lacking. We describe an interactive, workshop‐driven, 2‐day short course that we constructed for pharmaceutical research personnel to learn these skills. The examples in the course and the workshop datasets source from our professional experiences, the scientific literature, and the mass media. During the course, the participants are exposed to and gain hands‐on experience with the principles of visual and graphical perception, design, and construction of both graphic and tabular displays of quantitative and qualitative information. After completing the course, with a critical eye, the participants are able to construct, revise, critique, and interpret graphic and tabular displays according to an extensive set of guidelines. Copyright © 2013 John Wiley & Sons, Ltd.     

New High-Speed Computing Devices

“One method of error analysis (not the one we will use) is based upon the principles of mathematical statistics. Unfortunately, statistical methods can only be meaningfully applied when one has large amounts of data for a given system. In many cases … these large quantities of data are not available … then statistical methods are not applicable, and some other methods must be devised.”     

基于核和灰度的双重异构数据序列预测建模方法研究

通过建立灰色异构数据"核"序列的DGM(1,1)模型,实现双重异构数据"核"的预测;以"核"为基础、以双重异构数据序列中较大的区间灰数信息域作为预测结果的信息域,构建基于区间灰数与实数的双重异构数据序列灰色预测模型,有效地将灰色预测模型建模对象从"同质数据"拓展至"双重异构数据"。研究成果对丰富灰色预测模型理论体系具有积极意义。     

知识共享对供应链信用风险传染的影响研究

将企业间知识共享这一因素引入供应链上下游企业博弈过程,在完全信息条件下研究三级供应链中零售商分别与分销商、制造商进行知识共享时知识共享量与企业信用风险水平和供应链信用风险传染强度之间的关系,并结合算例进行了数值分析.基于Stackelberg博弈模型的研究结果表明,供应链上的知识共享有助于降低供应链成员企业的信用风险;进行知识共享的企业间信用风险传染强度随着知识共享量的增加而增大;企业进行知识共享比不进行知识共享时受到其它企业信用风险传染的影响大.     

我国行业分类与国际标准行业分类的比较研究

 本文通过对我国行业分类和国际标准行业分类两项分类标准最新版本的比较,对两项分类的基本构成、应用原则、门类和大类的条目结构以及对照转换等方面的情况进行了比较分析研究。详细解析了在若干行业领域中,二者存在典型差异的情况。最后,对我国的行业分类的科学性和国际可比性做出了分析评价,对如何进一步提升分类水平提出了改进意见,另外还提出了未来修订的思路和方法等建议。     

长三角科技资源配置能力与城市化进程的协调耦合关系研究

科技资源配置能力已成为长江地区城市化进程的重要推力。因此,在构建科技资源与城市化耦合系统评价指标体系的基础上,利用耦合协调度模型综合评价长江区域科技资源配置与城市化的交互耦合关系。结果显示:从时间维度看,研究期内长三角科技资源配置能力与城市化进程之间的耦合关系基本上处于磨合阶段,耦合协调度以低度协调耦合状态为主并逐步过渡到中度协调耦合状态;从空间维度看,长三角各城市的科技资源配置与城市化耦合协调度在极度协调耦合、高度协调耦合、中度协调耦合、低度协调耦合四个阶段均有分布,层级分明且大部分城市尚处于低度协调耦合状态。     

基于目标导向的银行理财产品最优费率研究

建立基于银行目标导向的理财产品费率模型,通过对不同目标下银行行为的讨论,得出理财产品费率调整的一个分析框架。研究发现：存在使银行的经济效益和社会效益综合提升程度最大的最优理财产品费率;最优费率不是固定值,而是一个动态概念;单纯考虑经济效益时,银行将调高理财产品费率;银行调高理财产品费率,将提升自身综合目标的实现程度;银行调低理财产品费率,并不改变银行的综合目标。     

基于改进D—S证据理论的TOPSIS模型在科技奖励评价中的应用

针对科技奖励评价的特点,根据改进D—S证据合成规则,将专家的评价指标值转化为指标的综合得分并形成决策矩阵;结合TOPSIS模型求解理想解和负理想解,计算距离和贴近度,对各评价项目进行综合排名。实证结果表明：该模型能够很好地解决科技奖励评价过程中的不确定性问题,为科技奖励综合评价提供了一种新的思路。     

Bounded influence estimation for regression and scale

Bednarski and Müller [Optimal bounded influence regression and scale M-estimators in the context of experimental design, Statistics 35 (2001), pp. 349–369] introduced a class of bounded influence M estimates for the simultaneous estimation of regression and scale in the linear model with normal errors by solving the corresponding normal location and scale problem at each design point. This limits the proposal to regressor distributions with finite support. Based on their approach, we propose a slightly extended class of M estimates that is not restricted to finite support and is numerically easier to handle. Moreover, we employ the even more general class of asymptotically linear (AL) estimators which, in addition, is not restricted to normal errors. The superiority of AL estimates is demonstrated by numerical comparisons of the maximum asymptotic mean-squared error over infinitesimal contamination neighbourhoods.     

Analysis of hybrid censored competing risks data

In this paper, we consider the analysis of hybrid censored competing risks data, based on Cox's latent failure time model assumptions. It is assumed that lifetime distributions of latent causes of failure follow Weibull distribution with the same shape parameter, but different scale parameters. Maximum likelihood estimators (MLEs) of the unknown parameters can be obtained by solving a one-dimensional optimization problem, and we propose a fixed-point type algorithm to solve this optimization problem. Approximate MLEs have been proposed based on Taylor series expansion, and they have explicit expressions. Bayesian inference of the unknown parameters are obtained based on the assumption that the shape parameter has a log-concave prior density function, and for the given shape parameter, the scale parameters have Beta–Gamma priors. We propose to use Markov Chain Monte Carlo samples to compute Bayes estimates and also to construct highest posterior density credible intervals. Monte Carlo simulations are performed to investigate the performances of the different estimators, and two data sets have been analysed for illustrative purposes.