工程总承包企业价值链及其优势分析

介绍了价值链理论以及价值链分析方法,并以此为基础,分析了工程总承包企业内部价值链、传统施工企业价值链、设计单位价值链以及建筑业在传统条件及工程总承包条件下的产业价值链。通过价值链分析,对工程总承包企业的成本优势、独特性优势及其来源进行阐述,指出了发展工程总承包企业是建筑企业发展的可取之道。     

A hierarchical model for extreme wind speeds

Summary.  A typical extreme value analysis is often carried out on the basis of simplistic inferential procedures, though the data being analysed may be structurally complex. Here we develop a hierarchical model for hourly gust maximum wind speed data, which attempts to identify site and seasonal effects for the marginal densities of hourly maxima, as well as for the serial dependence at each location. A Gaussian model for the random effects exploits the meteorological structure in the data, enabling increased precision for inferences at individual sites and in individual seasons. The Bayesian framework that is adopted is also exploited to obtain predictive return level estimates at each site, which incorporate uncertainty due to model estimation, as well as the randomness that is inherent in the processes that are involved.     

Using a Markov Chain to Construct a Tractable Approximation of an Intractable Probability Distribution

Abstract.  Let π denote an intractable probability distribution that we would like to explore. Suppose that we have a positive recurrent, irreducible Markov chain that satisfies a minorization condition and has π as its invariant measure. We provide a method of using simulations from the Markov chain to construct a statistical estimate of π from which it is straightforward to sample. We show that this estimate is 'strongly consistent' in the sense that the total variation distance between the estimate and π converges to 0 almost surely as the number of simulations grows. Moreover, we use some recently developed asymptotic results to provide guidance as to how much simulation is necessary. Draws from the estimate can be used to approximate features of π or as intelligent starting values for the original Markov chain. We illustrate our methods with two examples.     

Maximum Likelihood Estimation in Gaussian Chain Graph Models under the Alternative Markov Property

Abstract.  The Andersson–Madigan–Perlman (AMP) Markov property is a recently proposed alternative Markov property (AMP) for chain graphs. In the case of continuous variables with a joint multivariate Gaussian distribution, it is the AMP rather than the earlier introduced Lauritzen–Wermuth–Frydenberg Markov property that is coherent with data-generation by natural block-recursive regressions. In this paper, we show that maximum likelihood estimates in Gaussian AMP chain graph models can be obtained by combining generalized least squares and iterative proportional fitting to an iterative algorithm. In an appendix, we give useful convergence results for iterative partial maximization algorithms that apply in particular to the described algorithm.     

大学生英语听力训练模式数据分析及学习策略的思考

本文就大学生听力训练的三种学习模式进行了实验,并结合认知学习论和“母语—英语知识—认知双元结构”的相关理论,对实验的相关数据进行了分析,同时,针对不同的学生提出了不同的学习策略和教学模式。     

构建阅读文库，培养学生自主阅读模式——一项英语专业阅读课教改实验报告

阅读是英语教学和学习中的重要环节,它不仅仅是阅读主体对文字符号的表层结构进行解读,更重要的是理解语义的深层结构.阅读过程是阅读主体、语言能力、阅读材料、阅读模式及背景知识相互作用的结果.阅读主体的背景知识越丰富,阅读能力就越强.     

两代大师的风范--刘永济、程千帆两先生的学术与人格

刘永济、程千帆两代国学大师的治学之道 ,其特点是由博返约、厚积薄发 ,文献考据与理论批评相结合 ,“知”与“能”相统一 ;他们人格高尚 ,忠诚教育事业 ,尊师重教 ,奖掖后进     

Bayesian Survival Analysis Using Bernstein Polynomials

Abstract.  Bayesian survival analysis of right-censored survival data is studied using priors on Bernstein polynomials and Markov chain Monte Carlo methods. These priors easily take into consideration geometric information like convexity or initial guess on the cumulative hazard functions, select only smooth functions, can have large enough support, and can be easily specified and generated. Certain frequentist asymptotic properties of the posterior distribution are established. Simulation studies indicate that these Bayes methods are quite satisfactory.     

2005兵临城下：超市规模之外的较量

本文从价值链演化的角度对竞争的新重点进行了论述,希望对不断扩张中的超市有所借鉴。     

Bayesian estimation in Kibble's bivariate gamma distribution

The authors describe Bayesian estimation for the parameters of the bivariate gamma distribution due to Kibble (1941). The density of this distribution can be written as a mixture, which allows for a simple data augmentation scheme. The authors propose a Markov chain Monte Carlo algorithm to facilitate estimation. They show that the resulting chain is geometrically ergodic, and thus a regenerative sampling procedure is applicable, which allows for estimation of the standard errors of the ergodic means. They develop Bayesian hypothesis testing procedures to test both the dependence hypothesis of the two variables and the hypothesis of equal means. They also propose a reversible jump Markov chain Monte Carlo algorithm to carry out the model selection problem. Finally, they use sets of real and simulated data to illustrate their methodology.