Rényi entropy of m-generalized order statistics

Abstract

Characterizing relations via Rényi entropy of m-generalized order statistics are considered along with examples and related stochastic orderings. Previous results for common order statistics are included.     

Inference and Decision Making for 21st-Century Drug Development and Approval

ABSTRACT

The cost and time of pharmaceutical drug development continue to grow at rates that many say are unsustainable. These trends have enormous impact on what treatments get to patients, when they get them and how they are used. The statistical framework for supporting decisions in regulated clinical development of new medicines has followed a traditional path of frequentist methodology. Trials using hypothesis tests of “no treatment effect” are done routinely, and the p-value < 0.05 is often the determinant of what constitutes a “successful” trial. Many drugs fail in clinical development, adding to the cost of new medicines, and some evidence points blame at the deficiencies of the frequentist paradigm. An unknown number effective medicines may have been abandoned because trials were declared “unsuccessful” due to a p-value exceeding 0.05. Recently, the Bayesian paradigm has shown utility in the clinical drug development process for its probability-based inference. We argue for a Bayesian approach that employs data from other trials as a “prior” for Phase 3 trials so that synthesized evidence across trials can be utilized to compute probability statements that are valuable for understanding the magnitude of treatment effect. Such a Bayesian paradigm provides a promising framework for improving statistical inference and regulatory decision making.     

Beyond tail median and conditional tail expectation: Extreme risk estimation using tail Lp-optimization

The conditional tail expectation (CTE) is an indicator of tail behavior that takes into account both the frequency and magnitude of a tail event. However, the asymptotic normality of its empirical estimator requires that the underlying distribution possess a finite variance; this can be a strong restriction in actuarial and financial applications. A valuable alternative is the median shortfall (MS), although it only gives information about the frequency of a tail event. We construct a class of tail L^p-medians encompassing the MS and CTE. For p in (1,2), a tail L^p-median depends on both the frequency and magnitude of tail events, and its empirical estimator is, within the range of the data, asymptotically normal under a condition weaker than a finite variance. We extrapolate this estimator and another technique to extreme levels using the heavy-tailed framework. The estimators are showcased on a simulation study and on real fire insurance data.     

无意识心理活动与科学创造

无意识是一种不为意识所知的特殊心理活动,在科学创造中起着非常重要的作用.本文试就无意识心理活动与科学创造的关系问题加以探讨,重点分析无意识的深隐性、可解性、偶现性的内在和谐以及三者之间的和谐互动在科学创造中的作用.     

"两个环节,一个主体"是做好大学生思想工作的基础

从国际国内和大学生的自身情况看,必须进行"两个环节,一个主体"的教育。两个环节,是指心理素质和道德素质的教育。心理素质是一种内在因素,是人的精神动力;道德素质是伦理价值的外在表现,是人的行为规范坐标;一个主体,是指对大学生坚定不移地进行邓小平理论和"三个代表"重要思想的教育,这是教育的灵魂和方向。     

开发我国人力资源创新能力的对策研究

创新是推动社会发展的动力 ,特别是在知识经济时代 ,一个国家竞争能力的强弱主要依赖于创新 ,而创新源于具有创新能力的人才。笔者从分析影响人力资源创新能力的心理因素和社会环境因素入手 ,针对这些影响因素提出了开发我国人力资源创新能力的对策。     

试论美国电影中的英雄情结

“英雄类”影片是好莱坞制造的最具轰动效应的神话之一。本文拟对美国影片中塑造的各类英雄形象加以梳理与阐释 ,并进而对这些英雄片背后的英雄情结进行剖析 ,以期管窥美国影片中一些深层文化心理机制     

Modelling daily multivariate pollutant data at multiple sites

Summary. This paper considers the spatiotemporal modelling of four pollutants measured daily at eight monitoring sites in London over a 4-year period. Such multiple-pollutant data sets measured over time at multiple sites within a region of interest are typical. Here, the modelling was carried out to provide the exposure for a study investigating the health effects of air pollution. Alternative objectives include the design problem of the positioning of a new monitoring site, or for regulatory purposes to determine whether environmental standards are being met. In general, analyses are hampered by missing data due, for example, to a particular pollutant not being measured at a site, a monitor being inactive by design (e.g. a 6-day monitoring schedule) or because of an unreliable or faulty monitor. Data of this type are modelled here within a dynamic linear modelling framework, in which the dependences across time, space and pollutants are exploited. Throughout the approach is Bayesian, with implementation via Markov chain Monte Carlo sampling.     

Computing maximum likelihood estimates from type II doubly censored exponential data

It is well-known that, under Type II double censoring, the maximum likelihood (ML) estimators of the location and scale parameters, θ and δ, of a twoparameter exponential distribution are linear functions of the order statistics. In contrast, when θ is known, theML estimator of δ does not admit a closed form expression. It is shown, however, that theML estimator of the scale parameter exists and is unique. Moreover, it has good large-sample properties. In addition, sharp lower and upper bounds for this estimator are provided, which can serve as starting points for iterative interpolation methods such as regula falsi. Explicit expressions for the expected Fisher information and Cramér-Rao lower bound are also derived. In the Bayesian context, assuming an inverted gamma prior on δ, the uniqueness, boundedness and asymptotics of the highest posterior density estimator of δ can be deduced in a similar way. Finally, an illustrative example is included.     

话题转换的顺应性研究

根据顺应理论,使用语言的过程是一个进行选择的过程,语言使用者不仅选择语言形式,同时还选择使用策略。话题转换现象是对社会规约和心理世界的一种顺应。话题转换不当,会产生负面影响,妨碍交际的进行。