民营经济的资金需求：陕西个案研究

在对陕西4个地市进行调研的基础上,估算了该省民营经济的资金需求总量,并分析了其资金需求的结构。结果表明,民营经济的资金存在需求总量难以满足和供求结构失衡的矛盾,在目前国有金融体系支持有限的情况下,民营经济对民间资本产生了强烈的需求。因此解决民营经济融资困境的出路在于有效搭建民间资本投入到民营经济的桥梁和通道。     

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.     

基于贝叶斯神经网络的非参数回归

提高神经网络模型推广能力的关键是控制模型的复杂度。该文探索了贝叶斯神经网络的非参数回归的建模方法,通过融入模型参数的先验知识,在给定数据样本及模型假设下进行后验概率的贝叶斯推理,使用马尔可夫链蒙特卡罗算法来优化模型控制参数,实现了对神经网络模型中不同部分复杂度的控制,获得了模型参数的后验分布及预测分布。在5个含噪二维函数回归问题上的应用显示了模型的复杂度能根据数据的复杂度而自适应调整,并给出了较好的预测结果。     

基于马尔可夫链的产品市场保有量预测模型

售后服务机构为了准确地准备库存,都需要预测产品的市场保有量。基于马尔可夫链建立的状态概率矩阵模型,与抽样调查、时间序列法、回归分析法等方法相比,更能准确预测市场产品保有量。与传统产品相比较,更新换代速度快的电子产品,要预测其市场保有量,更需要利用状态概率矩阵模型。     

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or change to one of the remainingK-2 categories; in addition, it is usually the case that the rating of some bonds is withdrawn during the time interval considered in the analysis.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.     

信息条件下的城市运输规划方法

交通网络中信息的引入,改变了以往人们的出行行为。常规的出行需求预测模型在信息条件下,需要进行合理改进。本文提出了将传统的出行产生模型与动态交通模拟模型集成进行信息条件下的城市运输规划研究的一种新的方法框架     

福利资源的开发:由资金资源向人力资源的转变

福利需求是多元化的需求 ,除了物质上的需求外 ,还有制度、心理、服务等方面的需求 ,所以 ,福利资源也具有多元性。过去我们只注意在资金上开发福利资源 ,忽视其他资源的利用 ,特别是忽视了人力资源的开发 ,使我国社会福利和保障事业的发展受到限制。因此 ,如何将人力资源转变成有效的福利资源 ,是我国今后福利事业发展的重大课题。     

基于灰色理论的房地产市场需求分析

运用灰色系统理论，建立了基于灰色关联熵的房地产市场需求影响因素分析模型，并用实例进行计算，为房地产市场需求分析提供了一种新方法，从而进一步完善了房地产市场评价体系。     

乡镇企业家的供求问题研究

市场制度的建立程度、企业创立条件的高低以及企业家人力资本产权的受保护程度影响乡镇企业家的需求与供给 ,导致乡镇企业创新乏力和资产流失。健全乡镇企业家成长的市场环境和制度环境 ,建立有效的激励机制 ,是保证乡镇企业家的有效需求和供给的真正解决办法。