Measuring the complexity of generalized linear hierarchical models

Measuring a statistical model's complexity is important for model criticism and comparison. However, it is unclear how to do this for hierarchical models due to uncertainty about how to count the random effects. The authors develop a complexity measure for generalized linear hierarchical models based on linear model theory. They demonstrate the new measure for binomial and Poisson observables modeled using various hierarchical structures, including a longitudinal model and an areal‐data model having both spatial clustering and pure heterogeneity random effects. They compare their new measure to a Bayesian index of model complexity, the effective number p_D of parameters (Spiegelhalter, Best, Carlin & van der Linde 2002); the comparisons are made in the binomial and Poisson cases via simulation and two real data examples. The two measures are usually close, but differ markedly in some instances where p_D is arguably inappropriate. Finally, the authors show how the new measure can be used to approach the difficult task of specifying prior distributions for variance components, and in the process cast further doubt on the commonly‐used vague inverse gamma prior.     

AN ALGORITHMIC APPROACH TO BAYESIAN LINEAR MODEL CALCULATIONS

A framework is described for organizing and understanding the computations necessary to obtain the posterior mean of a vector of linear effects in a normal linear model, conditional on the parameters that determine covariance structure. The approach has two major uses; firstly, as a pedagogical tool in the derivation of formulae, and secondly, as a practical tool for developing computational strategies without needing complicated matrix formulae that are often unwieldy in complex hierarchical models. The proposed technique is based upon symbolic application of the sweep operator SWP to an appropriate tableau of means and covariances. The method is illustrated with standard linear model specifications, including the so-called mixed model, with both fixed and random effects.     

FL115离心式机油滤清器的特性研究与试验分析

建立了分流离心式滤清器转速特性和液力特性的数学模型.通过试验得到FL115离心式滤清器在不同喷嘴口径以及不同温度工况下的转速特性曲线和液力特性曲线,以及滤清效率.分析了转子转速、驱动流量和进油压力三者之间的关系,推出了设计喷嘴的最佳口径范围.通过理论数据与试验数据的比较,证明了该数学模型可以作为研发离心式滤清器的设计参考.     

试论足球专项速度耐力影响因素数学模型的建立

根据专项速度耐力水平高低与测试及其影响因素，提出用数学模型方法来简化这些问题，以达到更有效、更科学地控制运动员专项速度耐力的训练．数学模型的建立反映了运动员对专项速度耐力各影响因素综合能力     

论治理模式下行政法对社会公共组织的权力规范问题

政府-市场-公民社会相互协作的治理模式，对于我国解决改革开放过程中所出现的行政机构膨胀、政企不分、政事不分以及推进社会主义民主政治建设等，都具有积极的借鉴意义。探讨了在治理模式下社会公共组织在我国的发展，并从法理和行政法功能两个角度论证了将其纳入行政法规范范围的依据，提出了几点具体的建议。     

非对称信息下证券公司道德风险定价模型的研究

由于证券市场上非对称信息状态的存在,信息差别给证券投资者保护制度带来了不容忽视的道德风险结果,本文通过建立证券公司道德风险定价模型,计算出了证券公司向证券投资者保护基金机构缴纳保护基金的费率基准。据此,在保护证券投资者利益的基础上,证券投资者保护基金机构可以向证券公司按照给出的费率基准收取保护基金,从而减少证券公司道德风险的发生。     

陕甘宁边区的劳模运动及其启示

20世纪40年代初中期，中国共产党在陕甘宁边区发起了一场声势浩大的劳动英雄和模范工作者运动。劳模运动对陕甘宁边区的新民主主义建设尤其是生产建设发挥了重要作用：它是边区发展生产和各项建设工作的一种新的、比较有效的组织形式和工作方法；它改变了群众的劳动观念，使“劳动光荣”深入人心，从根本上提高了人民的生产积极性；它是改进工作、培养干部和联系群众的运动，是边区生产和各项工作发展的推动力。总结其经验教训，对于社会主义建设尤其是社会主义新农村建设，具有重要意义。     

垂直一体化的安全猪肉生产模式探析—以四川铁骑力士集团公司为例

本文以垂直一体化理论为依据，从交易费用方面系统分析了垂直一体化安全猪肉生产的原因，通过对四川铁骑力士集团公司“公司＋园区＋农户”的垂直一体化生产模式的实证分析，得出垂直一体化生产是公司、农户、政府、消费者共赢的模式。     

Prediction in Some Poisson Errors in Variables Models

Predictive distributions are developed and illustrated for prediction in some Poisson errors in variables models. Two different situations in which multiplicative treatment effects are appropriate are considered within the context of predicting counts of road accidents. Hierarchical prior structures are investigated, and numerical integration and Gibbs sampling routines are used to derive the predictive and posterior probabilities. Examples of analyses are provided with data from road accidents in Sweden.     

论新形势下高校学习型研究生会的创建

研究生教育的快速发展对高校研究生管理提出了新的要求,也更加凸显了研究生会的作用和地位;但当前研究生会由于自身的缺陷不能完全适应新形势的要求。将学习型组织的"五项修炼"模型作为理论基础,分析了当前高校研究生会存在的缺陷,并提出创建学习型研究生会的具体措施,以增强其组织绩效,促进其自我管理、自我教育、自我服务作用的发挥。