基于知识链的管理

论述了知识链的有关概念和特点,通过分析以往的知识链模型,提出了改进的知识链模型;对知识链管理的机制进行了分析;从控制论的角度,对知识链内部知识成长的机制进行了分析,并指出知识链内部知识转移的影响因素,为知识管理的发展提供了一定的理论依据。     

A general inverse sampling scheme and its application to adaptive cluster sampling

Not having a variance estimator is a seriously weak point of a sampling design from a practical perspective. This paper provides unbiased variance estimators for several sampling designs based on inverse sampling, both with and without an adaptive component. It proposes a new design, which is called the general inverse sampling design, that avoids sampling an infeasibly large number of units. The paper provide estimators for this design as well as its adaptive modification. A simple artificial example is used to demonstrate the computations. The adaptive and non‐adaptive designs are compared using simulations based on real data sets. The results indicate that, for appropriate populations, the adaptive version can have a substantial variance reduction compared with the non‐adaptive version. Also, adaptive general inverse sampling with a limitation on the initial sample size has a greater variance reduction than without the limitation.     

汉代边郡军粮廪给问题探讨

粮食供给是军队后勤给养中的一项重要内容。汉代边塞地区军粮主要供给吏卒及其家属,也用于借贷和马、牛、驼、狗之食。从量制、时制、身份差别、劳动强度和年龄、性别等方面,分析了军队吏卒和吏卒家属口粮分等廪给的具体情况及其影响要素,从而揭示出汉代军粮供给体制的内在规律。正是由于汉代军粮廪给有章可循,才最大限度地提高了后勤的供应能力和军队的战斗力,保证了军队平时守土卫边和战时有效打击来犯之敌。     

Improving Convergence of the HastingsMetropolis Algorithm with an Adaptive Proposal

The HastingsMetropolis algorithm is a general MCMC method for sampling from a density known up to a constant. Geometric convergence of this algorithm has been proved under conditions relative to the instrumental (or proposal) distribution. We present an inhomogeneous HastingsMetropolis algorithm for which the proposal density approximates the target density, as the number of iterations increases. The proposal density at the n th step is a non-parametric estimate of the density of the algorithm, and uses an increasing number of i.i.d. copies of the Markov chain. The resulting algorithm converges (in n ) geometrically faster than a HastingsMetropolis algorithm with any fixed proposal distribution. The case of a strictly positive density with compact support is presented first, then an extension to more general densities is given. We conclude by proposing a practical way of implementation for the algorithm, and illustrate it over simulated examples.     

哈尔滨市发展绿色食品产业集群的基本条件与优势

产业集群对集群内企业在竞争力提升上有重要作用。哈尔滨市发展绿色食品产业集群,具有得天独厚的地理环境和资源优势,具有大企业集团集中、高校和科研院所较多的优势,及在国内外市场上的品牌和信誉优势。通过绿色食品产业集群的发展壮大,必将提高产品与企业的市场竞争力,推动绿色食品产业的持续发展。     

Estimating rating transition probabilites with missing data

In this article we provide a rigorous treatment of one of the central statistical issues of credit risk management. GivenK-1 rating categories, the rating of a corporate bond over a certain horizon may either stay the same or change to one of the remainingK-2 categories; in addition, it is usually the case that the rating of some bonds is withdrawn during the time interval considered in the analysis. When estimating transition probabilities, we have thus to consider aK-th category, called withdrawal, which contains (partially) missing data. We show how maximum likelihood estimation can be performed in this setup; whereas in discrete time our solution gives rigorous support to a solution often used in applications, in continuous time the maximum likelihood estimator of the transition matrix computed by means of the EM algorithm represents a significant improvement over existing methods.     

On Block Updating in Markov Random Field Models for Disease Mapping

Gaussian Markov random field (GMRF) models are commonly used to model spatial correlation in disease mapping applications. For Bayesian inference by MCMC, so far mainly single-site updating algorithms have been considered. However, convergence and mixing properties of such algorithms can be extremely poor due to strong dependencies of parameters in the posterior distribution. In this paper, we propose various block sampling algorithms in order to improve the MCMC performance. The methodology is rather general, allows for non-standard full conditionals, and can be applied in a modular fashion in a large number of different scenarios. For illustration we consider three different applications: two formulations for spatial modelling of a single disease (with and without additional unstructured parameters respectively), and one formulation for the joint analysis of two diseases. The results indicate that the largest benefits are obtained if parameters and the corresponding hyperparameter are updated jointly in one large block. Implementation of such block algorithms is relatively easy using methods for fast sampling of Gaussian Markov random fields ( Rue, 2001 ). By comparison, Monte Carlo estimates based on single-site updating can be rather misleading, even for very long runs. Our results may have wider relevance for efficient MCMC simulation in hierarchical models with Markov random field components.     

蒂布特模型启迪下的可流动公共产品供给

中国目前正处于城乡公共产品统筹供给的关键时期,研究符合中国国情的公共产品供给理论具有重要意义。蒂布特模型是关于公共产品供给机制的理论研究,其政策含义是政府要采取促进居民流动的方式来提高公共产品的配置效率。由于该模型所作假设的现实性较弱,其结论和应用有一定局限性。根据流动程度,可以把公共产品划分为可流动公共产品和不可流动公共产品两类,可以通过可流动公共产品的流动来提高公共产品的配置效率。中国目前在城乡可流动公共产品优化配置方面有较大发展空间。     

供应链企业间的合作轨道模型

文章主要介绍了轨道模型在供应链企业合作中的应用 ,根据合作程度的不同 ,伙伴企业处于以核心企业为中心的不同轨道。文章分别从静态和动态的角度运用轨道模型分析了企业间合作关系以及这种合作关系的变化。一方面使企业间的合作问题简单化 ;另一方面 ,轨道模型便于对合作问题进行深入的定量化研究。     

基于需求不确定性的供应链库存控制研究

通过建立需求不确定性环境下供应链成员的独立存货成本模型,运用模拟退火法对该模型进行52周的仿真,求解存货最佳订购数量与最佳再订购点,从而比较出不同存货控制策略的供应链存货总成本及订单满足率的差异。