A Population Approach to Analysis of Variance Models

Several authors have contributed to what can now be considered a rather complete theory for analysis of variance in cases with orthogonal factors. By using this theory on an assumed basic reference population, the orthogonality concept gives a natural definition of independence between factors in the population. By looking upon the treated units in designed experiments as a formal sample from a future population about which we want to make inference, a natural parametrization of expectations and variances connected to such experiments arises. This approach seems to throw light upon several controversial questions in the theory of mixed models. Also, it gives a framework for discussing the choice of conditioning in models     

Generalized Leverage and its Applications

The generalized leverage of an estimator is defined in regression models as a measure of the importance of individual observations. We derive a simple but powerful result, developing an explicit expression for leverage in a general M -estimation problem, of which the maximum likelihood problems are special cases. A variety of applications are considered, most notably to the exponential family non-linear models. The relationship between leverage and local influence is also discussed. Numerical examples are given to illustrate our results     

Efficient Estimation of a Distribution Function under Quadrant Dependence

LetX₁,X₂, ..., be real-valued random variables forming a strictly stationary sequence, and satisfying the basic requirement of being either pairwise positively quadrant dependent or pairwise negatively quadrant dependent. LetF^ be the marginal distribution function of theX_ips, which is estimated by the empirical distribution functionF_n and also by a smooth kernel-type estimateF_n, by means of the segmentX₁, ...,X_n. These estimates are compared on the basis of their mean squared errors (MSE). The main results of this paper are the following. Under certain regularity conditions, the optimal bandwidth (in the MSE sense) is determined, and is found to be the same as that in the independent identically distributed case. It is also shown thatn MSE(F_n(t)) andnMSE (F^_n(t)) tend to the same constant, asn→∞ so that one can not discriminate be tween the two estimates on the basis of the MSE. Next, ifi(n) = min {k∈{1, 2, ...}; MSE (F_k(t)) ≤ MSE (F_n(t))}, then it is proved thati(n)/n tends to 1, asn→∞. Thus, once again, one can not choose one estimate over the other in terms of their asymptotic relative efficiency. If, however, the squared bias ofF^_n(t) tends to 0 sufficiently fast, or equivalently, the bandwidthh_n satisfies the requirement thatnh³_n→ 0, asn→∞, it is shown that, for a suitable choice of the kernel, (i(n) ?n)/(nh_n) tends to a positive number, asn→∞ It follows that the deficiency ofF_n(t) with respect toF^_n(t),i(n) ?n, is substantial, and, actually, tends to ∞, asn→∞. In terms of deficiency, the smooth estimateF^_n(t) is preferable to the empirical distribution functionF_n(t)     

On the shrinkage of local linear curve estimators

Local linear curve estimators are typically constructed using a compactly supported kernel, which minimizes edge effects and (in the case of the Epanechnikov kernel) optimizes asymptotic performance in a mean square sense. The use of compactly supported kernels can produce numerical problems, however. A common remedy is ridging, which may be viewed as shrinkage of the local linear estimator towards the origin. In this paper we propose a general form of shrinkage, and suggest that, in practice, shrinkage be towards a proper curve estimator. For the latter we propose a local linear estimator based on an infinitely supported kernel. This approach is resistant against selection of too large a shrinkage parameter, which can impair performance when shrinkage is towards the origin. It also removes problems of numerical instability resulting from using a compactly supported kernel, and enjoys very good mean squared error properties.     

Estimation of critical points in the mixture inverse Gaussian model

The maximum likelihood estimation for the critical points of the failure rate and the mean residual life function are presented in the case of mixture inverse Gaussian model. Several important data sets are analyzed from this point of view. For each of the data sets, Bootstrapping is used to construct confidence intervals of the critical points.     

唯物辩证法视阈下新时代社会主要矛盾变化探析

唯物辩证法是理解新时代社会主要矛盾变化的哲学前提。在唯物辩证法视阈下,党的十九大报告提出的社会主要矛盾变化是主观辩证法与客观辩证法互动的历史性结论,内涵着唯物辩证法意蕴,是新时代标志、丰富内涵与创新性工作要求的有机统一。在时代价值维度,社会主要矛盾变化标志着中国特色社会主义发展的阶段性质变、中国社会主义现代化战略目标的转变、中国特色社会主义走向世界舞台中心的国际地位变化;在思想内涵维度,新时代社会主要矛盾变化集中体现为矛盾条件的客观性变化、矛盾因素的共时性变化、矛盾关系的根本性变化,需要辩证性的理解;在工作方法维度,社会主要矛盾变化对工作实践提出了新的发展理念、新的问题关切以及弘扬创新工作精神等创新性要求。     

论社会主义市场经济的三个根本问题

坚持和发展社会主义市场经济,必须紧紧抓住和解决好基本制度、生产目的和资源配置这三个根本问题.这三个根本问题也构成了中国特色社会主义政治经济学的核心内容.在基本制度方面,必须坚持公有制主体地位不能动摇,国有经济主导作用不能动摇;坚持按劳分配为主体、使改革发展成果更多更公平惠及全体人民.在生产目的上,要满足广大人民日益增长、不断升级和个性化的物质文化和生态环境需要.在解放和发展生产力的同时,保证被解放和发展了的生产力归人民所有,走可持续发展道路.在资源配置方面,社会主义国家由于有公有制经济的全力配合,政府对资源配置才能真正发挥“看得见的手”的作用,当然其效果如何还得看这只手有没有遵循经济发展的客观规律.中国特色社会主义追求的是共同富裕,公有制的存在和发展保证了经济发展成果由人民群众共享,从而中国特色社会主义的效率必然是也必须是最广大人民群众的效率,从而这个效率必然是与公平一致的.     

习近平治国理政的哲学方法论探略

党的十八大以来,以习近平同志为核心的党中央立足当代中国、把握世界大势,提出了一系列治国理政的新理念新思想新战略,有力推动中国特色社会主义进入新时代,形成了习近平新时代中国特色社会主义思想。习近平总书记高度重视学习和掌握辩证唯物主义和历史唯物主义,将其视为中国共产党人的“看家本领”。马克思主义哲学为习近平治国理政提供了总的方法论遵循。辩证唯物主义特别是其中的实事求是的实践观、事物联系发展的观点、具体问题具体分析的矛盾观提供了思维方法的总依据;历史唯物主义关于人民主体地位的思想和群众路线群众观点则贯穿于其治国理政全过程,彰显着中国共产党的价值自觉、理论自觉与实践自觉,奠定了习近平治国理政新理念新思想新战略的整个基石。     

中小学教师依法治教的困境与对策

中小学教师是依法治教的实践者、宣讲者、推动者,是推动依法治教的关键因素之一。但是,在中小学教师依法治教的过程中,还存在着中小学教师法治素养良莠不齐,教育立法滞后、执法不严、司法不公以及中小学教师职前、职后法治教育缺失等现象。全面推进依法治国,实现教育治理体系和治理能力现代化,必须深刻把握和充分发挥中小学教师在依法治教中的价值和作用,增强其依法治教的自觉性;必须深刻分析中小学教师在依法治教中面临的各种困境与原因,采取针对性措施,做到有的放矢,综合施策。     

拟人绘本和真人绘本对幼儿人格教育效果的影响： 一项挑战传统观念的国外心理学实验的启示

绘本阅读是幼儿成长过程中的一种有效教育途径。绘本中的角色类型会影响绘本对幼儿的教育效果。笔者基于国外一项心理学实验,并结合其他相关实验,介绍拟人绘本和真人绘本对幼儿人格和知识学习影响的研究,从幼儿心理学角度分析了真人绘本在教育效果上优于拟人绘本的心理机制。最后,阐述了关于拟人绘本和真人绘本的几点思考。