The covariance of the backward and forward recurrence times in a renewal process: the stationary case and asymptotics for the ordinary case

In a Poisson process, it is well-known that the forward and backward recurrence times at a given time point t are independent random variables. In a renewal process, although the joint distribution of these quantities is known (asymptotically), it seems that very few results regarding their covariance function exist. In the present paper, we study this covariance and, in particular, we state both necessary and sufficient conditions for it to be positive, zero or negative in terms of reliability classifications and the coefficient of variation of the underlying inter-renewal and the associated equilibrium distribution. Our results apply either for an ordinary renewal process in the steady state or for a stationary process.     

Diagnostics of multiple group influential observations for logistic regression models

In this paper, two new multiple influential observation detection methods, GCD.GSPR and mCD*, are introduced for logistic regression. The proposed diagnostic measures are compared with the generalized difference in fits (GDFFITS) and the generalized squared difference in beta (GSDFBETA), which are multiple influential diagnostics. The simulation study is conducted with one, two and five independent variable logistic regression models. The performance of the diagnostic measures is examined for a single contaminated independent variable for each model and in the case where all the independent variables are contaminated with certain contamination rates and intensity. In addition, the performance of the diagnostic measures is compared in terms of the correct identification rate and swamping rate via a frequently referred to data set in the literature.     

On comparing,classifying and clustering several dependent regression models

Classifying several regression models fitted on a dataset is one of the most problems in data analysis. In other words, scientists are interested in comparing several regression models that can be used for a dataset. In this paper, an approach will be used to compare and classify several dependent regression models. Then the performance of the proposed method is investigated using simulation study and real example.     

属性集容量确定的夹挤式测度模式及其推算模型

迄今,为解决多属性偏好关联决策属性集容量判断指数复杂性难题所提出的λ模糊测度模式与k-可加模糊测度模式,以及建构在它们之上的属性集容量确定的推算模型,尚存在着适用性差的技术不足。为此,以平衡容量判断的可操作性和容量推算的准确性为视角,提出了一种新容量测度模式,即关于容量判断与推算的夹挤式测度模式,并在此基础上通过引入决策者较易判断给出的容量序信息构建了相应的容量推算模型。基于数值模拟的对比分析表明：新模式不仅在应用可行性上高于k-可加模糊测度模式,而且从容量推算的准确性上看也明显优于λ模糊测度模式和k-可加模糊测度模式,因而对实际决策具有更强的适用性。     

基于心智模型的恐怖主义袭击扩展式演化博弈分析

政府反恐措施与恐怖分子袭击手段存在着相互观察、适应性演化的过程。本文首先构建了政府作为先行动者、恐怖分子作为后行动者的斯塔克伯格博弈模型,进一步建立了恐怖袭击问题的扩展式演化博弈模型。由于扩展式演化博弈的均衡分析需要考虑代际内和代际间不同层次的信念学习,造成了演化分析的复杂性。本文将"心智模型"概念引入到演化博弈,采取了心智模型演化解的分析方法,得出了简化后的演化均衡解。最后,结合新疆墨玉县6.28暴恐事件进行算例分析,比较怀特流形演化解和心智模型演化解的差异。心智模型演化解的结果表明,根据恐怖分子群体中选择袭击比例是否高于临界值,政府策略收敛到防御或者不防御。该求解方法通过将普遍接受的社会规范引入到演化过程分析,不仅简化了怀特流形的分析过程,而且均衡解展示了更为丰富的、更为切合实际管理问题的演化特征。     

目标导向层次分析方法

对含有抽象属性的多属性层次结构而言,层次分析法即AHP（包括DIS-AHP、ABS-AHP、IDE-AHP和SUP-AHP四种具体方法）会因比率比较基准缺失、权重内涵模糊不清或方案评价不保序而缺乏科学理性。为发展AHP,基于摆幅置权（SW）判断模式和多属性决策属性价值公度方法,首先给出了能为层次结构抽象属性上的SW判断提供支持的规约性多属性决策属性价值公度方法,然后由此并结合多属性价值理论给出了能够克服现有层次分析法内在缺陷的目标导向层次分析方法即ToAHP。相对于AHP,ToAHP在判断模式与权重内涵、方法建构的理论基础和相关假设检验、方案评价保序与其内在数理依据上具有明显的相对科学合理性。应用分析表明：在输入信息可比的条件下,ToAHP明显优于AHP的四种分析方法之中最具可信性的SUP-AHP方法。     

基于供需平衡的农民非农就业模式探析

解决三农问题的关键之一是农村剩余劳动力的非农就业问题。农民非农就业模式应着眼于实现政府、企业与农民三者的联动。政府应使产业结构合理化,并加大对农村的投入力度,实现城乡协调发展。中小企业要保持竞争优势,增加非农就业需求农民应提高就业能力,向劳动力市场提供有效供给。     

产品差异化对市场结构的影响分析——基于演化经济学的观点

以双占垄断为例,产品差异化对市场结构的影响具有以下几个方面:(1)完全垄断可能是同质产品竞争的结果;(2)尽管产品差异化不能排除完全垄断的存在,但是从长期看,它极大增加了厂商共存的可能性;(3)产品差异化程度越大,双占寡头的结构越稳定。     

不同的电力交易模式对电力市场均衡的影响分析

本文采用经济学理论中的局部均衡分析方法,对目前电力市场交易中普遍采用的电力库与双边交易下可能形成的电力市场均衡,包括均衡价格与均衡数量形成进行了比较分析。得出的初步结论:一是电力交易模式的设计对电力市场结构的形成有直接影响;二是均衡电价的形成受到垄断势力影响,并向有利于垄断势力强的一方变动;三是相对于双边交易而言,电力库下的市场垄断势力更强。     

信息技术课程多元智力教学模式探究

多元智力理论超越了传统以语言——数理逻辑能力为中心的智力观念,它的发展对传统学科教育产生了深刻的影响,本文就信息技术课程学科特点,从多元智力角度对教学方法改革进行探讨和研究。