经理人激励的细分: 隐藏行动、努力成本和风险厌恶

本文研究经理人隐藏行动、努力成本和风险厌恶态度对经理人激励的影响.本文的研究基于标准委托人-代理人模型,但放松其关于经理人行动不能影响企业风险的假定,而采用更接近现实的假定--企业风险至少部分内生于经理人的行动.通过研究,本文将经理人激励明确细分类为努力增进激励(βeffort激励)和追求风险激励(βrisk激励)两类.为实现βeffort激励,经理人报酬只需是企业业绩的线性函数即可;但为实现βrisk激励,经理人报酬应是企业业绩的凸函数.     

基于伪最近邻节点的异构无线网络组网实现及仿真

网络的出现,改变了很多人工作和生活的习惯,作为现代信息技术的基础,网络技术的发展速度很快,传统的有线网络已经开始很少使用,在实际的网络建设中,主要采用新兴的无线网络,本文在伪最近邻节点概念的基础上,对ISIS等网络传输协议进行了分析,最后对基于伪最近邻节点的异构无线网络组网实现及仿真,进行了深入的研究.     

断裂与重构:少数民族地区学校教育中的潜在课程研究

本文所探讨的潜在课程重点在于“潜在”上,目的是想说明在少数民族地区现代性学校教育中的潜在课程是如何存在的,它潜在地发挥着什么样的作用。经研究发现,潜在课程与少数民族文化是一种冲突的关系,表现出了“断裂”与“重构”的文化现象。因此,本文主要从这两个方面探讨潜在课程对于少数民族文化和个体的潜在作用:作为文化断裂,类似于强制地要求停止你以前的思考和习惯;身份重构则要求你必须获得与以往不同的身份和意识,并先适应学校中生活和现代性要求。     

存款保险制度研究与中国的选择

为了维持银行业的稳定发展,许多国家建立了由存款保险制度、最后贷款人制度和审慎监管三大要素组成的金融安全网。目前我国已建立了最后贷款人制度,并专门成立了中国银监会来负责对银行业的监管,但存款保险制度至今仍处于酝酿阶段。为何中国进入存款保险制度需要如此漫长的经历呢?本文将试述存款保险制度的优缺点及我国为何迟迟才准备建立存款保险的原因。     

生命力的飞跃和突进--评王度庐的小说《卧虎藏龙》

《卧虎藏龙》具有心理悲剧的特征.女主人公玉娇龙的性格是在八方受敌、四面出击的境遇下展现的,其中包括"善"与"善"的冲突.这一形象的深刻之处在于作者充分揭示了她内心的、性格的矛盾,在这个意义上,最大的"敌人"正是她自己.小说对玉娇龙的悲剧及其与生俱来、伴随终身的孤独感的渲染,得力于王度庐的审美追求与精神分析派美学的契合.以刘泰保为代表的"闾巷之侠"形象的生动性,则体现着作者的"平民主义"精神.根据小说原著改编的同名电影和从小说节选的《语文读本》教材也各有特色.     

工程训练中安全隐患的分析与预防

在高等教育工程训练教学中,对存在的安全隐患因素进行分析,通过对安全事故采取有效的预防措施,对提高教学质量,确保教学过程安全进行有很大帮助。     

Qualitative longitudinal analysis of symptoms in patients with primary and metastatic brain tumours

Summary.  Primary and metastatic brain tumour patients are treated with surgery, radiation therapy and chemotherapy. Such treatments often result in short- and long-term symptoms that impact cognitive, emotional and physical function. Therefore, understanding the transition of symptom burden over time is important for guiding treatment and follow-up of brain tumour patients with symptom-specific interventions. We describe the use of a hidden Markov model with person-specific random effects for the temporal pattern of symptom burden. Clinically relevant covariates are also incorporated in the analysis through the use of generalized linear models.     

Hidden Markov Mixture Autoregressive Models: Stability and Moments

This article introduces a parsimonious structure for mixture of autoregressive models, where the weighting coefficients are determined through latent random variables, as functions of all past observations. These latent variables follow a Markov model. We propose a dynamic programming algorithm for forecasting, which reduces the volume of calculations. We also derive limiting behavior of unconditional first moment of the process and an appropriate upper bound for the limiting value of the variance. Further more, we show convergence and stability of the second moment. Finally, we illustrate the efficacy of the proposed model by simulation.     

Variational Bayes for estimating the parameters of a hidden Potts model

Hidden Markov random field models provide an appealing representation of images and other spatial problems. The drawback is that inference is not straightforward for these models as the normalisation constant for the likelihood is generally intractable except for very small observation sets. Variational methods are an emerging tool for Bayesian inference and they have already been successfully applied in other contexts. Focusing on the particular case of a hidden Potts model with Gaussian noise, we show how variational Bayesian methods can be applied to hidden Markov random field inference. To tackle the obstacle of the intractable normalising constant for the likelihood, we explore alternative estimation approaches for incorporation into the variational Bayes algorithm. We consider a pseudo-likelihood approach as well as the more recent reduced dependence approximation of the normalisation constant. To illustrate the effectiveness of these approaches we present empirical results from the analysis of simulated datasets. We also analyse a real dataset and compare results with those of previous analyses as well as those obtained from the recently developed auxiliary variable MCMC method and the recursive MCMC method. Our results show that the variational Bayesian analyses can be carried out much faster than the MCMC analyses and produce good estimates of model parameters. We also found that the reduced dependence approximation of the normalisation constant outperformed the pseudo-likelihood approximation in our analysis of real and synthetic datasets.     

论德国公司法中禁止隐性实物出资问题

隐性实物出资是指股东在公司设立或增资时 ,先将股金交给公司 ,然后向公司出售货物 ,并以收回货款的方式收回其缴纳的股金。隐性实物出资的目的是逃避注册法院对实物出资的法定审查 ,其结果是资本真实原则不能切实实施 ,公司本身的利益、小股东的利益尤其是公司债权人的利益可能会受到损害。因此这种出资安排为德国的司法实践所禁止。类似的问题在我国公司的出资实践中也同样存在 ,德国禁止隐性实物出资的做法可供我们借鉴