Diagnostics in elliptical regression models with stochastic restrictions applied to econometrics

We propose an influence diagnostic methodology for linear regression models with stochastic restrictions and errors following elliptically contoured distributions. We study how a perturbation may impact on the mixed estimation procedure of parameters in the model. Normal curvatures and slopes for assessing influence under usual schemes are derived, including perturbations of case-weight, response variable, and explanatory variable. Simulations are conducted to evaluate the performance of the proposed methodology. An example with real-world economy data is presented as an illustration.     

女性欲望的分裂与张扬--对张爱玲《心经》中女性形象的再认识

旨在探讨《心经》中独特的女性形象以及张爱玲写此文的深层原因。生活在父权制社会下,男性凝望世界中的女性,渴望直接与男性对话,从而产生异样感情,特殊的母女关系经历了分裂到张扬再到重组的过程,表现出女性在与男性相抗衡的过程中的绝望与疯狂,也隐含作者内心深处的希望。     

高校课程育人：本真、理路与评价

立德树人居于学校教育发展全局的核心位置,需要将其落实到课程育人的生动实践中。但是,在课程育人的具体实践中,仍有部分教师将其简单化为“课程+育人”的生硬结合,导致课程育人容易陷入理论教条窠臼。为此,高校教师应充分认识到高校课程育人在目标要求、重点内容、转型路径上的人性化、时代化和数字化本真意蕴,从教师素养、课程建设、课堂教学三个方面开展育人实践。在此基础上,针对具体课程的育人效果而言,可以从目标设定、内容选择、方法实施、结果呈现等方面进行评价,从而进一步推动课程育人的生动实践。     

普通高校公共体育教学的改革实验与结果分析

从体育课程设置、教学内容、教学组织形式、学生体育考核等方面对“三阶段式”体育教学改革进行分析,可以发现,“三阶段式”体育教学具有实效性,符合现阶段学生实际。由此也发现,体育教学方法、手段只有尽可能体现快乐健康教育的特点,才能取得好的教学效果。     

劳动力转移的困境和挑战——基于对凉山彝族外出务工人员困境的思考

目前,在凉山彝区,外出务工是劳动力转移的主要方式,许多家庭通过外出务工脱贫致富。在当地无力承担和消化剩余劳动力的情况下,外出务工的现象将长期存在,正确认识彝区劳动力转移的合理性非常必要。为此笔者对四川凉山的冕宁、盐源等地彝区外出务工人员较多的村寨通过田野调查方式,了解当地劳动力转移的历史和现状,掌握存在的问题并分析其原因,提出解决思路和具体措施。应该建立劳动力转移的社会支持系统,继续不懈地积极推进劳动力转移工作。继续加大各级职业技术教育,增强劳动力转移的市场竞争力。加强法制教育,促进用人机构和彝族群众增强法制意识,依法促进彝族务工者的城市融入。进一步强化乡镇劳务开发工作体系建设,加强跨区域合作,倡导有序输出,规范对劳务经纪人的管理,强化劳务培训质量,提高彝族务工人员素质,保护彝族务工人员的合法益。     

An elastic-net penalized expectile regression with applications

To perform variable selection in expectile regression, we introduce the elastic-net penalty into expectile regression and propose an elastic-net penalized expectile regression (ER-EN) model. We then adopt the semismooth Newton coordinate descent (SNCD) algorithm to solve the proposed ER-EN model in high-dimensional settings. The advantages of ER-EN model are illustrated via extensive Monte Carlo simulations. The numerical results show that the ER-EN model outperforms the elastic-net penalized least squares regression (LSR-EN), the elastic-net penalized Huber regression (HR-EN), the elastic-net penalized quantile regression (QR-EN) and conventional expectile regression (ER) in terms of variable selection and predictive ability, especially for asymmetric distributions. We also apply the ER-EN model to two real-world applications: relative location of CT slices on the axial axis and metabolism of tacrolimus (Tac) drug. Empirical results also demonstrate the superiority of the ER-EN model.     

马克思主义与当代中国经济学

传统社会主义经济学的弊端已被人们充分认识和批判。但是,我们在对传统社会主义经济学进行清算的时候,理应给予马克思主义以应有的评价。实践在发展,马克思主义也在不断发展。马克思主义对当代中国经济学的走向依然在发挥着重大影响,这个影响是如此真实,以至于在当代中国经济学所关注的所有重大问题中,无论人们承认与否,马克思主义的“幽灵”都无处不在。实践证明,中国经济学的发展和构建必须以马克思主义为基础。     

时光·梦想

生活在19世纪的人们,乐于听到工业革命的轰鸣声。他们知道,这是“现代”的召唤。21世纪的我们,现代的我们则渴望着回到自然的怀抱。这是文明的又一道曲线。它从一个欣欣向荣滑到另一个欣欣向荣。而这两个时代都打上了进步的鲜明烙印,都同样是我们光荣的、关于自身、关于梦想的珍贵记忆。如果好奇于日常生活中的周遭事务,并执着于探求它们的来源,我们会惊奇地发现:时常光顾的超市、购物中心、度假村、俱乐部,始于世界博览会;电视机、留声机、电灯,在世博会上首次展出;甚至第一台纺织机、第一架飞机竟也是从世博会步入我们的生活。“一切始于…     

A primal dual active set with continuation algorithm for high-dimensional nonconvex SICA-penalized regression

The smooth integration of counting and absolute deviation (SICA) penalty has been demonstrated theoretically and practically to be effective in nonconvex penalization for variable selection and parameter estimation. However, solving the nonconvex optimization problem associated with SICA penalty in high-dimensional setting remains to be enriched, mainly due to the singularity at the origin and the nonconvexity of the SICA penalty function. In this paper, we develop a fast primal dual active set (PDAS) with continuation algorithm for solving the nonconvex SICA-penalized least squares in high dimensions. Upon introducing the dual variable, the PDAS algorithm iteratively identify and update the active set in the optimization using both the primal and dual information, and then solve a low-dimensional least square problem on the active set. When combined with a continuation strategy and a high-dimensional Bayesian information criterion (BIC) selector on the tuning parameters, the proposed algorithm is very efficient and accurate. Extensive simulation studies and analysis of a high-dimensional microarray gene expression data are presented to illustrate the performance of the proposed method.     

A comparative study of confidence intervals to assess biosimilarity from analytical data

Assessment of analytical similarity of tier 1 quality attributes is based on a set of hypotheses that tests the mean difference of reference and test products against a margin adjusted for standard deviation of the reference product. Thus, proper assessment of the biosimilarity hypothesis requires statistical tests that account for the uncertainty associated with the estimations of the mean differences and the standard deviation of the reference product. Recently, a linear reformulation of the biosimilarity hypothesis has been proposed, which facilitates development and implementation of statistical tests. These statistical tests account for the uncertainty in the estimation process of all the unknown parameters. In this paper, we survey methods for constructing confidence intervals for testing the linearized reformulation of the biosimilarity hypothesis and also compare the performance of the methods. We discuss test procedures using confidence intervals to make possible comparison among recently developed methods as well as other previously developed methods that have not been applied for demonstrating analytical similarity. A computer simulation study was conducted to compare the performance of the methods based on the ability to maintain the test size and power, as well as computational complexity. We demonstrate the methods using two example applications. At the end, we make recommendations concerning the use of the methods.