Linearity of regression for non-adjacent record values

Let X₁,X₂,… be a sequence of iid random variables having a continuous distribution; by R₁,R₂,… denote the corresponding record values. All the distributions allowing linearity of regressions either E(R_m+k|R_m) or E(R_m|R_m+k) are identified.     

Point and confidence interval estimates for a global maximum via extreme value theory

The aim of this paper is to provide some practical aspects of point and interval estimates of the global maximum of a function using extreme value theory. Consider a real-valued function f:D→? defined on a bounded interval D such that f is either not known analytically or is known analytically but has rather a complicated analytic form. We assume that f possesses a global maximum attained, say, at u*∈D with maximal value x*=max _u  f(u)?f(u*). The problem of seeking the optimum of a function which is more or less unknown to the observer has resulted in the development of a large variety of search techniques. In this paper we use the extreme-value approach as appears in Dekkers et al. [A moment estimator for the index of an extreme-value distribution, Ann. Statist. 17 (1989), pp. 1833–1855] and de Haan [Estimation of the minimum of a function using order statistics, J. Amer. Statist. Assoc. 76 (1981), pp. 467–469]. We impose some Lipschitz conditions on the functions being investigated and through repeated simulation-based samplings, we provide various practical interpretations of the parameters involved as well as point and interval estimates for x*.     

A bayesian estimator for the dependence function of a bivariate extreme‐value distribution

Any continuous bivariate distribution can be expressed in terms of its margins and a unique copula. In the case of extreme‐value distributions, the copula is characterized by a dependence function while each margin depends on three parameters. The authors propose a Bayesian approach for the simultaneous estimation of the dependence function and the parameters defining the margins. They describe a nonparametric model for the dependence function and a reversible jump Markov chain Monte Carlo algorithm for the computation of the Bayesian estimator. They show through simulations that their estimator has a smaller mean integrated squared error than classical nonparametric estimators, especially in small samples. They illustrate their approach on a hydrological data set.     

A value of information framework for assessing the trade-offs associated with uncertainty,duration, and cost of chemical toxicity testing

A number of investigators have explored the use of value of information (VOI) analysis to evaluate alternative information collection procedures in diverse decision-making contexts. This paper presents an analytic framework for determining the value of toxicity information used in risk-based decision making. The framework is specifically designed to explore the trade-offs between cost, timeliness, and uncertainty reduction associated with different toxicity-testing methodologies. The use of the proposed framework is demonstrated by two illustrative applications which, although based on simplified assumptions, show the insights that can be obtained through the use of VOI analysis. Specifically, these results suggest that timeliness of information collection has a significant impact on estimates of the VOI of chemical toxicity tests, even in the presence of smaller reductions in uncertainty. The framework introduces the concept of the expected value of delayed sample information, as an extension to the usual expected value of sample information, to accommodate the reductions in value resulting from delayed decision making. Our analysis also suggests that lower cost and higher throughput testing also may be beneficial in terms of public health benefits by increasing the number of substances that can be evaluated within a given budget. When the relative value is expressed in terms of return-on-investment per testing strategy, the differences can be substantial.     

伟大建党精神的道德意涵及其价值

作为中国共产党人精神谱系形成和发展的“根”与“脉”,伟大建党精神有着丰富的道德意涵,彰显出人性的善与正义。伟大建党精神的赓续传承、贯彻落实及发扬光大必须借助伦理道德的力量,积极发挥人民群众的主动性与创造性。伟大建党精神的道德维度主要体现在4个层面:其一,坚持真理、坚守理想是伟大建党精神的道德信念;其二,践行初心、担当使命是伟大建党精神的道德实践;其三,不怕牺牲、英勇斗争是伟大建党精神的道德意志;其四,对党忠诚、不负人民是伟大建党精神的道德价值取向。这4个层面不是相互割裂的,而是一个结构严谨、逻辑严密的道德整体。伟大建党精神中内蕴的道德因素是支撑与推动中国共产党带领人民在革命与建设时期的伟大实践中不断实现接续胜利的重要动因,也是探知中国共产党百年党史整体性脉络图景内在逻辑不可忽视的重要内容。     

基于文献计量的价值共创研究现状分析

将CNKI和Web of Science作为中外文献数据源,通过文献计量法,从时间、地点、学科、研究层次、研究方向、关键词、引文等维度对国内外价值共创研究现状进行分析。在此基础上,总结出目前研究的三个显著特征：研究呈现出一定的阶段性特征;基础研究所占比例较大,实践、应用研究较少;价值共创的概念定义不清晰,有影响力的学术成果数量有限。     

习近平新时代中国特色社会主义思想的教育实践

为培养中国特色社会主义事业合格建设者和可靠接班人,以思政课的教育实践为例,对习近平新时代中国特色社会主义思想进行研究。研究认为,习近平总书记从民族复兴、党和国家事业发展以及建设中国特色社会主义教育强国的全局出发,高度重视教师队伍建设和教育工作;作为用习近平新时代中国特色社会主义思想铸魂育人的中坚力量,思政课教师要在学生心里埋下真善美的种子,始终做学生立德铸魂的引路人;思政课教师要坚持不懈地传播马克思主义科学理论,用习近平新时代中国特色社会主义思想武装师生头脑,引领学生坚定理想信念,补足“精神之钙”,始终做政治清醒的明白人;要引领学生弘扬中国精神,锚定成长成才的“压舱石”,特别要在指导学生贯通学好“四史”,涵育家国情怀和培养创新实践能力方面下功夫;要引领学生培育和践行社会主义核心价值观,在学思悟践中掌握马克思主义科学思辩的方法论精髓和实践要义,切实解决好世界观、人生观、价值观这个“总开关”问题,帮助学生“扣好人生第一粒扣子”。     

新会计准则下金融衍生品的风险管理

本文从金融衍生品的风险出发,主要介绍了金融衍生品风险的定义、分类,包括市场风险、流动性风险、操作风险、法律风险,信用风险,结合新会计准则,阐述了金融衍生品新的特点,如金融衍生品核算办法的改变,金融衍生工具使用难度较大、金融衍生品披露的改变,并在建立及时有效的信息披露制度、加强内部控制和风险管理、完善我国金融衍生品市场建设、提高投资者素质等方面提出了一些关于如何更好地进行金融衍生品风险管理的建议。     

农产品网购意愿影响因素及作用机理研究——基于参照效应视角的分析

以整合型科技接受和使用模型(UTAUT)和价值接受模型(VAM)为基础,通过构建参照群体、参考价格、积极在线评论与感知价值、感知风险以及购买意愿之间的关系模型,从参照效应视角实证分析了农产品网购意愿的影响因素及作用机理,并探讨了消费者农产品质量与安全意识在参照效应影响网购意愿中的调节作用.结果表明:参照效应对农产品网购意愿有显著影响;感知价值和感知风险在参照效应影响网购意愿中均发挥了中介作用,但感知价值的中介作用显著大于感知风险;消费者农产品质量与安全意识在参照效应影响网购意愿中部分地发挥了调节效应.其中,对参照群体和积极在线评论的调节效应显著,即网购过程中,消费者越是重视农产品质量与安全,参照群体的意见和积极在线评论对其网购意愿的影响就会越凸显.     

全球化对大学生社会主义核心价值观教育的影响

社会主义核心价值体系作为一种社会文化和价值形态的总和,并不是孤立存在,其必然受到一定社会经济、政治、文化背景的影响。当前在经济全球化大环境下,大学生社会主义核心价值体系教育需要正确分析全球化的实质,准确把握大学生的思想动态,增强社会主义核心价值体系教育的实效性。