重庆市都市区人中就业现状及变化趋势

都市区作为重庆经济的核心区域,随着经济的快速发展以及城市化进程的加快,正对人口产生巨大的聚集效应,而人口就业将成为一个十分突出的问题。因此,准确把握劳动力供求变动趋势十分重要。为此通过模型运算,对2000-2020年的都市区劳动年龄人口和劳动力的供求变动趋势进行了预测分析。     

中日城市供水系统静态效率的对比研究

文章运用DEA方法，评价了北京、东京、上海以及横滨等城市2003年-2005年间供水系统的静态效率，发现日本三个城市供水系统的效率要高于中国三个城市的效率，造成这种状况的原因主要在于中国的水价体系还不够完善，供水企业收益不能完全回收其成本。     

Markov chain Monte Carlo methods for high dimensional inversion in remote sensing

Summary.  We discuss the inversion of the gas profiles (ozone, NO₃, NO₂, aerosols and neutral density) in the upper atmosphere from the spectral occultation measurements. The data are produced by the 'Global ozone monitoring of occultation of stars' instrument on board the Envisat satellite that was launched in March 2002. The instrument measures the attenuation of light spectra at various horizontal paths from about 100 km down to 10–20 km. The new feature is that these data allow the inversion of the gas concentration height profiles. A short introduction is given to the present operational data management procedure with examples of the first real data inversion. Several solution options for a more comprehensive statistical inversion are presented. A direct inversion leads to a non-linear model with hundreds of parameters to be estimated. The problem is solved with an adaptive single-step Markov chain Monte Carlo algorithm. Another approach is to divide the problem into several non-linear smaller dimensional problems, to run parallel adaptive Markov chain Monte Carlo chains for them and to solve the gas profiles in repetitive linear steps. The effect of grid size is discussed, and we present how the prior regularization takes the grid size into account in a way that effectively leads to a grid-independent inversion.     

协同运输管理运行机制研究

协同运输管理是在CPFR基础上发展起来的一种供应链管理方法。它通过降低供应链中的运输成本、缩短商品交付时间和提高准时交货率,实现供应链价值的最大化。协同运输管理的有效实施,需要建立完善的运行机制,包括动力机制、约束机制、实际行为和惩罚机制,并配备相应的软硬件条件。     

BAYESIAN SUBSET SELECTION AND MODEL AVERAGING USING A CENTRED AND DISPERSED PRIOR FOR THE ERROR VARIANCE

This article proposes a new data‐based prior distribution for the error variance in a Gaussian linear regression model, when the model is used for Bayesian variable selection and model averaging. For a given subset of variables in the model, this prior has a mode that is an unbiased estimator of the error variance but is suitably dispersed to make it uninformative relative to the marginal likelihood. The advantage of this empirical Bayes prior for the error variance is that it is centred and dispersed sensibly and avoids the arbitrary specification of hyperparameters. The performance of the new prior is compared to that of a prior proposed previously in the literature using several simulated examples and two loss functions. For each example our paper also reports results for the model that orthogonalizes the predictor variables before performing subset selection. A real example is also investigated. The empirical results suggest that for both the simulated and real data, the performance of the estimators based on the prior proposed in our article compares favourably with that of a prior used previously in the literature.     

Discrete time modelling of disease incidence time series by using Markov chain Monte Carlo methods

Summary.  A stochastic discrete time version of the susceptible–infected–recovered model for infectious diseases is developed. Disease is transmitted within and between communities when infected and susceptible individuals interact. Markov chain Monte Carlo methods are used to make inference about these unobserved populations and the unknown parameters of interest. The algorithm is designed specifically for modelling time series of reported measles cases although it can be adapted for other infectious diseases with permanent immunity. The application to observed measles incidence series motivates extensions to incorporate age structure as well as spatial epidemic coupling between communities.     

论新文学思潮与新文学流派的动态关系

新文学思潮与新文学流派之间因果莫辨、源流纠缠的动态关系 ,充分证明了近百年来新文学思潮与新文学流派本身非线性、非对称的生存状态。所谓非线性与非对称 ,其实质就是不稳定性和不成熟性 ,它们直接制约着新文学近百年发展进程 ,使之在历时态和共时态上始终呈现出某种程度的不良生存状态和发展趋势。     

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。     

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.