关于广义远达问题的适定性

设C是实Banach空间X中有界闭凸子集且0是C的内点,PC(·)是关于C的Minkowski泛函.设K是Banach空间X中非空闭的有界相对弱紧子集.对X中的点x,称最大化问题maxC(x,K)为适定的是指存在唯一的(z)∈K使得pC((z)-x)=uC(x,K)和每一满足limnn→∞pC(zn-x)=uC(x,K)的序列{zn}(∈)K均强收敛到(z),其中uC(x,K)=supz∈KpC(z-x).在C是严格凸和Kadec的假定下,证得了使得最大化问题maxC(x,k)为适定的所有x∈X的全体组成的集合X0(K)是X中的剩余集.进一步,如果关于Pc(·)的凸性模是严格正的,K是X中闭的有界子集,证明了集X\X0(K)是X中的σ-多孔集.这些本质地推广和延拓了包括De Blasi等,Fitzpatrick,Panda和Kapoor,Li和作者等人结果在内的近期相应结果.     

A_p－权函数与VMO的一个关系定理

对满足Ａ_ｐ（１＜Ｐ＜∞）条件的函数进行了讨论，得出的Ａ_ｐ权函数与ＶＭＯ（ｖａｎｉｓｈｉｎｇｍｅａｎｏｓｃｉｌｌａｔｉｏｎ）关系的几个定理，推广了文［１］中的结论。     

Bounded-influence rank estimation in the linear model

We introduce and study a class of rank-based estimators for the linear model. The estimate may be roughly described as being calculated in the same manner as a generalized M-estimate, but with the residual being replaced by a function of its signed rank. The influence function can thus be bounded, both as a function of the residual and as a function of the carriers. Subject to such a bound, the efficiency at a particular model distribution can be optimized by appropriate choices of rank scores and carrier weights. Such choices are given, with respect to a variety of optimality criteria. We compare our estimates with several others, in a Monte Carlo study and on a real data set from the literature.     

本期执行编辑

研究了一类二阶泛函微分方程 ,给出了方程的振动解有界性的判定定理 .     

解释论下盗窃罪与抢夺罪界分标准之匡正

对于盗窃罪与抢夺罪的界分标准,理论界一直存在争议,传统观点以秘密性和公然性作为区别盗窃罪和抢夺罪的关键,而有学者提出的平和窃取说则主张以行为是否具有暴力性作为区分之标准.以解释论为研究视角,通过对盗窃和抢夺两词进行文理解释、目的解释、体系解释和比较解释,主张应当坚持传统观点,反对平和盗窃说,将秘密窃取作为盗窃罪的客观构成要件;认为盗窃罪与抢夺罪的主要区别在于盗窃行为具有秘密性,抢夺行为具有公然性,对于行为人误认为未被财物所有人和保管人发现的情况,应当按照盗窃罪处理.     

高管团队分析框架下的组织错误研究

随着人误研究的不断深入,研究对象也由个体转向组织,这为人误研究提供了新的方向,以往关于组织失误的研究主要局限于组织管理因素对人因事故的作用与影响方面,对于组织内部各因素对人因事故的影响力却缺乏研究。组织高层管理团队是由在组织中主要承担战略决策职责的高层管理者所组成的团队,是决定组织发展和影响组织绩效的核心群体,对组织错误具有决定性影响作用,在人因事故中扮演着重要角色。这里通过高管团队起源、假设、研究不足与固有局限分析,从高管团队视角对组织错误展开研究,期待为组织错误提供新的分析框架与研究视角。     

Optimally robust credible sets with a class of priors

We determine a credible set A   that is the “best” with respect to the variation of the prior distribution in a neighborhood Γ$\Gamma$ of the starting prior _π0(θ)${\pi }_0(\theta )$. Among the class of sets with credibility γ$\gamma$ under _π0${\pi }_0$, the “optimally robust” set will be the one which maximizes the minimum probability of including θ$\theta$ as the prior varies over Γ$\Gamma$. This procedure is also Γ-minimax$\Gamma \text{-minimax}$ with respect to the risk function, probability of non-inclusion. We find the optimally robust credible set for three neighborhood classes Γ$\Gamma$, the ε-contamination$\epsilon \text{-contamination}$ class, the density ratio class and the density bounded class. A consequence of this investigation is that the maximum likelihood set is seen to be an optimal credible set from a robustness perspective.     

协同创新、知识溢出的演化博弈机制研究

基于演化博弈理论,研究企业、大学和科研机构间协同创新过程的"演化稳定策略"。通过设计知识共享模型分析知识投入与知识溢出对协同创新的影响并进行仿真检验。研究认为,长期的协同创新中"合作"策略是参与方采用的"演化稳定策略";当参与方数量不同时,小群体一方率先实现"合作"策略稳定,群体数量相近时双方采用"合作"策略的收敛速度趋于一致;增加知识溢出有利于提高协同创新效率与稳定性。在理论上解释了协同创新博弈的合作策略稳定性,为产学研合作的机制设计提供决策参考。     

Trimmed mean and bounded influence estimators for the parameters of the ar(1) process

Trimmed mean type estimators are proposcd for estimating the parameters of an AR(1) process. Thcsc definitions are then extended to bounded influence trimmed mcans in analogy to those in the regression case. The behaviour of the estimators are studied numerically under two

outlicr generating models.