Correlation in a Bayesian framework

The authors consider the correlation between two arbitrary functions of the data and a parameter when the parameter is regarded as a random variable with given prior distribution. They show how to compute such a correlation and use closed form expressions to assess the dependence between parameters and various classical or robust estimators thereof, as well as between p‐values and posterior probabilities of the null hypothesis in the one‐sided testing problem. Other applications involve the Dirichlet process and stationary Gaussian processes. Using this approach, the authors also derive a general nonparametric upper bound on Bayes risks.     

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.     

基于灰色聚类的企业伦理能力评价研究

分析了企业伦理能力测度理论现状,提出了企业伦理能力评价指标体系。运用灰色聚类理论建立了相应的企业伦理能力评价模型,并运用该模型对海尔集团企业伦理现状进行了定量分析。     

对我国全面取消农业税的几点思考

政府全面取消农业税这一重要举措有其深刻的背景,虽然对全面取消农业税的必要性已成基本共识,但还是有人对取消农业税产生疑虑,因此要理性看待全面取消农业税。我国免征农业税后要走出“先减后升”的怪圈,免征农业税关键是要减轻农民的“灰色负担”,减免农业税后还要做好相应配套的工作。     

商业信用风险管理绩效影响因素的实证分析

近年来,Jianmin Jia等学者对"我国信用风险管理现状"及其相关问题进行研究,取得一定的研究成果,但相应研究中存在着"简单使用线性回归,未能消除变量间的相互影响"等局限。基于对已有相关研究成果的评析,并运用因子分析和Pearson相关分析方法,对我国商业信用风险管理绩效的影响因素进行实证研究。研究表明:商业信用风险管理绩效的关键影响因素为"信用管理职能设置"、"客户资信评估"和"信用政策制定",我国企业应从"完善信用风险管理职能"、"改善信息不对称状况"和"提高信用政策制定水平"三方面提高风险管理绩效。     

基于共同持有资产的银行间接关联网络研究

金融市场是一个复杂系统,银行之间不仅有直接的拆借关系,还能够通过投资市场建立间接关联。本文分析了资产内生相关性、资产降价出售以及银行投资行为等因素对银行间接关联程度的影响,基于这些因素通过持有共同资产构建银行系统的间接关联,并以此为基础通过平面极大过滤图方法生成银行间接关联网络,论证了该网络中的系统重要性银行,并通过对该网络结构特征的分析,发现间接关联网络具有小世界和无标度等特征,这些特征与银行通过直接拆借形成的网络相似。本文对于银行间接关联网络的研究不仅能够更加清晰地了解银行之间的关系,也为银行系统性风险的监管提供了新的视角。     

基于灰粗集属性知识简约算法的海运规则发现

海运市场运营规则能够帮助海运企业找到盈利增长点,针对海运市场营运规则难于被发现的问题,将灰色系统理论和粗糙集理论进行融合,针对知识约简中分辨函数范式转化过程中的逻辑推演难题,提出了一种基于灰色粗集融合属性的改进约简算法,选取2007年、2010年、2013年、2015年典型年份作为样本年份,应用灰色系统、粗糙集和基于灰粗集知识约简算法分别进行海运市场盈运规则发现实证分析,通过比较证明了该算法的时效性,同时发掘出了当前海运市场的船型、货品、航线、运价、运力间的营运管理规则。     

医学教育中隐性课程的相关性研究

近年来,隐性课程的研究成为一个热点问题,特别是在高等教育领域备受关注。从教育界对隐性课程的研究角度（隐性课程的概念、特征、功能、建设与管理几个方面）切入,对实践中存在的一些问题进行分析,以期对以后的研究有所帮助。     

A copula-based Markov chain model for the analysis of binary longitudinal data

A fully parametric first-order autoregressive (AR(1)) model is proposed to analyse binary longitudinal data. By using a discretized version of a copula, the modelling approach allows one to construct separate models for the marginal response and for the dependence between adjacent responses. In particular, the transition model that is focused on discretizes the Gaussian copula in such a way that the marginal is a Bernoulli distribution. A probit link is used to take into account concomitant information in the behaviour of the underlying marginal distribution. Fixed and time-varying covariates can be included in the model. The method is simple and is a natural extension of the AR(1) model for Gaussian series. Since the approach put forward is likelihood-based, it allows interpretations and inferences to be made that are not possible with semi-parametric approaches such as those based on generalized estimating equations. Data from a study designed to reduce the exposure of children to the sun are used to illustrate the methods.     

Quantile dispersion graphs to compare the efficiencies of cluster randomized designs

The purpose of this article is to compare efficiencies of several cluster randomized designs using the method of quantile dispersion graphs (QDGs). A cluster randomized design is considered whenever subjects are randomized at a group level but analyzed at the individual level. A prior knowledge of the correlation existing between subjects within the same cluster is necessary to design these cluster randomized trials. Using the QDG approach, we are able to compare several cluster randomized designs without requiring any information on the intracluster correlation. For a given design, several quantiles of the power function, which are directly related to the effect size, are obtained for several effect sizes. The quantiles depend on the intracluster correlation present in the model. The dispersion of these quantiles over the space of the unknown intracluster correlation is determined, and then depicted by the QDGs. Two applications of the proposed methodology are presented.