On sequential Monte Carlo sampling methods for Bayesian filtering

In this article, we present an overview of methods for sequential simulation from posterior distributions. These methods are of particular interest in Bayesian filtering for discrete time dynamic models that are typically nonlinear and non-Gaussian. A general importance sampling framework is developed that unifies many of the methods which have been proposed over the last few decades in several different scientific disciplines. Novel extensions to the existing methods are also proposed. We show in particular how to incorporate local linearisation methods similar to those which have previously been employed in the deterministic filtering literature; these lead to very effective importance distributions. Furthermore we describe a method which uses Rao-Blackwellisation in order to take advantage of the analytic structure present in some important classes of state-space models. In a final section we develop algorithms for prediction, smoothing and evaluation of the likelihood in dynamic models.     

Time series analysis of non-Gaussian observations based on state space models from both classical and Bayesian perspectives

The analysis of non-Gaussian time series by using state space models is considered from both classical and Bayesian perspectives. The treatment in both cases is based on simulation using importance sampling and antithetic variables; Markov chain Monte Carlo methods are not employed. Non-Gaussian disturbances for the state equation as well as for the observation equation are considered. Methods for estimating conditional and posterior means of functions of the state vector given the observations, and the mean-square errors of their estimates, are developed. These methods are extended to cover the estimation of conditional and posterior densities and distribution functions. The choice of importance sampling densities and antithetic variables is discussed. The techniques work well in practice and are computationally efficient. Their use is illustrated by applying them to a univariate discrete time series, a series with outliers and a volatility series.     

企业并购估值贴现现金流模型研究

威斯通模型是企业并购估值贴现现金流模型中具有代表性的研究。文章针对威斯通模型讨论了企业是否具有真正增长机会的条件;研究了企业在超常增长期采取不同投资策略对其价值的影响,建立了新的估值模型,并对两种模型在估值上的差异进行了分析。     

中国滨海旅游城市入境旅游流量及潜力——基于旅游地引力模型的实证分析

在Crampon基本引力模型基础上,引入更多反映旅游地吸引力及两地点因素的变量,构建滨海型旅游地引力模型。用最小二乘法对2009年截面数据进行回归分析,结果显示:影响我国滨海旅游地引力的因素主要有客源地GDP、旅游地旅游从业人数、旅游地GDP、旅游地宣传促销努力程度、客源地与旅游地间的距离、文化认同感以及签证政策,而客源地人口数量和旅游地景区、酒店数量对游客流量解释力度不大。并利用回归方程估算各旅游地的旅游潜力进行测算,通过旅游流量实际值和潜力值的比较,将所有滨海型旅游地分为三类,每一类旅游地应根据分类选择相应发展对策。     

四川民族地区人口流动与城市化发展路径研究

本文以阿坝州、甘孜州、凉山州为例,分析了四川民族地区人口流动的成因、意义与困境;人口流动与城市化发展存在互动关系．积极推进民族地区城市化进程是缓解人口流动困境的有效路径。     

In search of experiential knowledge

In recent years, the concept of “experiential knowledge” has increasingly been used to characterize the distinctive contribution patients make to decision-making in the health field. Even though it seems well-nigh impossible to characterize it precisely, there is no doubting its significance for decision-making contexts ranging from the individual to the political. Since individual experiences of any condition or treatment differ widely, whose experiences come to constitute “knowledge”? In this paper, I argue that, rhetoric notwithstanding, numerous constraints “filter” the experiences which come to function as “experiential knowledge”. Looking to the future of health care, likely to be marked by growing inequalities, I suggest that a reflection on the notion of experiential knowledge leads to two challenges for social scientists.     

改进型INTER-IMIG桨搅拌槽内流场的PlV实验研究

针对二维粒子图像测速技术( particle image velocimetry,PIV)的局限性,利用三维粒子成像测速技术(PIV)对改 进型INTER-MIG桨搅拌槽流的轴向速度、径向速度、切向速度的分布进行研究,介绍了三维PIV系统的结构组成,再利 用二维PIV对流场进行流线分析。结果表明：无挡板时,槽内的流体受到了较强的剪切作用,而轴向速度与径向速度相 对较小,整体的混合效果较差;有挡板时,流体的轴向和径向速度明显提高,增加了流体湍动效应。挡板破坏了流体内部 的有序流动,桨叶前端的涡流也明显减弱     

国际资本流动与我国经济增长:1984～2005

国际资本流动对经济增长有正面效应和负面效应。对于我国而言,从短期来看,国际资本流动促进了经济增长;从长期来说,经济增长吸引外资流入,又让外资流入推动经济增长。现阶段,我国应该给予外资国民待遇,有利于我国经济持续、稳定和健康发展。     

辽宁沿海经济带与内陆腹地互动发展的实证研究

基于城市流强度模型和经济联系强度模型,对辽宁沿海经济带与内陆腹地的互动发展状况进行了分析,认为当前辽宁沿海经济带与内陆腹地的互动发展尚处于初级阶段,并且呈现出区域不均衡状态.因此,要加大政策倾斜和投资力度,充分发挥沿海经济带内引外联的作用,完善区域城市等级规模体系;在选择能带动当地经济发展的主导产业的基础上,建立围绕主导产业的行业间工会与协会;深化政府管理体制改革,加强软环境建设,推动辽宁沿海经济带与内陆腹地互动发展的顺畅进行.     

国内外石油市场的信息流动与一体化

文章采用2000年5月至2005年5月原油价格的日度数据,以美国西德克萨斯(WTI)和中国大庆为代表,研究了国内外石油市场的一体化问题.协整检验结果表明两个市场存在较强的一体化趋势.进一步选取均值和方差作为信息的代理变量,运用均值和方差的Granger因果检验考察了两个市场间的信息流动方向,结论表明信息都是从WTI流向大庆,意味着两个市场尚处于部分一体化的状态.较强的一体化趋势说明中国原油定价机制改革取得了一定的成功,但部分一体化意味着中国还只能被动接受国际油价的变动,却不能影响国际油价的变动.政策建议是应建立具有一定交易规模的石油期货市场,以提高中国在国际石油市场的影响力.