论分享价值原则的文化战略学意义--十八届三中全会《决定》的理论解读

在“五位一体”框架中，探讨支撑国家整体发展战略的基本价值原则，乃是当代中国化马克思主义文化战略学的重要课题之一。中共十八届三中全会《决定》强调“让一切劳动、知识、技术、管理、资本的活力竞相迸发”，要做到这一点，在市场之内的初次分配中，必须让“资本-劳动”分享利润，与此相对应的是一种与“平等”等密切相关的“分享”价值原则。《决定》有关“多渠道增加居民财产性收入”“保障农民公平分享土地增值收益”等重大举措，同样是在市场之内贯彻分享价值原则，而以民生为主的社会建设、以公共服务为主的文化事业则是在市场之外推行分享价值原则的主要方式。全面推行分享价值原则，既有利于坚定地推进新型市场化改革，同时也有利于保障平等、促进和谐、拓展自由，对内可以凝聚社会共识，激发国民创造力，对外则有助于在价值制高点上展现社会主义中国的文化魅力和感召力。     

美国公民教育方法对我国思政教育的启示

美国作为世界上最发达的资本主义国家，其公民教育是成功的，美国公民教育的成功源于其方法的成功。探究美国公民教育方法，借鉴其宝贵经验，对建立一套符合我国实际的思想政治教育方法体系，促进我国思想政治教育的健康发展，具有重要的现实意义。     

A comparative study of confidence intervals for negative binomial proportion

In this paper, we investigate four existing and three new confidence interval estimators for the negative binomial proportion (i.e., proportion under inverse/negative binomial sampling). An extensive and systematic comparative study among these confidence interval estimators through Monte Carlo simulations is presented. The performance of these confidence intervals are evaluated in terms of their coverage probabilities and expected interval widths. Our simulation studies suggest that the confidence interval estimator based on saddlepoint approximation is more appealing for large coverage levels (e.g., nominal level≤1% ) whereas the score confidence interval estimator is more desirable for those commonly used coverage levels (e.g., nominal level>1% ). We illustrate these confidence interval construction methods with a real data set from a maternal congenital heart disease study.     

Fitting the generalized lambda distribution to pre-binned data

Density estimation for pre-binned data is challenging due to the loss of exact position information of the original observations. Traditional kernel density estimation methods cannot be applied when data are pre-binned in unequally spaced bins or when one or more bins are semi-infinite intervals. We propose a novel density estimation approach using the generalized lambda distribution (GLD) for data that have been pre-binned over a sequence of consecutive bins. This method enjoys the high power of the parametric model and the great shape flexibility of the GLD. The performances of the proposed estimators are benchmarked via simulation studies. Both simulation results and a real data application show that the proposed density estimators work well for data of moderate or large sizes.     

现代社会隐私权和知情权的边界

现代社会是权利的社会,也是权利冲突频发的社会。权利之间的冲突缘起于法律规则的模糊性、权利的滥用和权利的交互性。其实质是一种客观存在的事实而非理论预设和逻辑分析的结果。权利冲突可以大致界分为主体间的权利冲突、价值冲突、利益冲突三种类型;权利间的冲突需要借助社会控制模式(个人控制、组织控制、法律控制)并通过价值平衡方法来解决。     

Bayesian penalized B-spline estimation approach for epidemic models

Ordinary differential equations (ODEs) are normally used to model dynamic processes in applied sciences such as biology, engineering, physics, and many other areas. In these models, the parameters are usually unknown, and thus they are often specified artificially or empirically. Alternatively, a feasible method is to estimate the parameters based on observed data. In this study, we propose a Bayesian penalized B-spline approach to estimate the parameters and initial values for ODEs used in epidemiology. We evaluated the efficiency of the proposed method based on simulations using the Markov chain Monte Carlo algorithm for the Kermack–McKendrick model. The proposed approach is also illustrated based on a real application to the transmission dynamics of hepatitis C virus in mainland China.     

服装系列设计方法之“抽象方程”论

通过长期的实践教学经验总结,将服装系列设计方法与数学方程联系在一起,形成服装系列设计的"抽象方程"理论,使服装系列设计具有了定向、定量、明确、有序的特征,力求寻找一条由简到繁、由易到难、循序渐进的学习实践方法,帮助服装设计初学者尽早摆脱设计瓶颈,步入设计正轨。     

1906-1908年的郑孝胥与预备立宪公会

考虑到我国未来年度的OD分布预测中的路网构成变化、区域经济布局变动、区域经济增长速度差异等一些具有时变性和特殊性因素，采用在“四阶段法”运量预测基础上改进而成的“三阶段法”进行高速铁路短期客运量预测。首先采用组合预测模型进行趋势运量预测，然后采用多元LOGIT模型进行方式分担，最后采用弹性系数诱增模型进行诱增运量预测。以京沪高铁为例，采用“三阶段法”预测了2014年和2015年京沪高铁本线及跨线单向客流量。     

Mean shift and influence measures in linear measurement error models with stochastic linear restrictions

We present influence diagnostics for linear measurement error models with stochastic linear restrictions using the corrected likelihood of Nakamura in 1990. The case deletion and mean shift outlier models are developed to identify outlying and influential observations. We derive a corrected score test statistic for outlier detection based on mean shift outlier models. The analogs of Cook's distance and likelihood distance are proposed to determine influential observations based on case deletion models. A parametric bootstrap procedure is used to obtain empirical distributions of the test statistics and a simulation study has been used to evaluate the performance of the proposed estimators based on the mean squares error criterion and the score test statistic. Finally, a numerical example is given to illustrate the theoretical results.