关于流动人口的伦理思考

国家统计局公布的2005年全国1%人口抽样调查数据显示,我国流动人口为14735万人,其中,跨省流动人口4779万人。与第五次全国人口普查相比,流动人口增加296万人,跨省流动人口增加537万人。1目前农村剩余劳动力仍有1.5亿~1.7亿人,大规模的劳动力流动将持续存在。按人口城镇化水平年均增长1个百分点测算,今后20年将有3亿农村人口陆续转化为城镇人口。北京市1%人口抽样调查显示,北京市2005年户籍人口为1180.7万人,流动人口为357.3万人,户籍人口与流动人口数量之比为3.3∶1。2大规模的人口流动为我国基础建设和城市发展做出了巨大的贡献,缓解了农村…     

林枝春的侨商情结

林枝春,祖籍福建省福清市,目前定居在辽宁省沈阳市法库经济开发区,现任辽宁省第十一届人大代表、辽宁省人大民族侨务外事委员会委员、辽宁省侨商联合会副会长、辽宁吉林黑龙江内蒙古自治区福建商会名誉会长、沈阳金宝慈善总会会长等职。他在香港注册成立了开宝庆福集团,投资中国、印尼、俄罗斯等地的全资、合资企业数十家,现任集团董事长。     

统计指数的贝叶斯方法

一、引言统计指数的编制是统计理论研究的一项重要内容,也是统计分析实践活动一项重要工具。近年来,统计指数在社会经济生活的各个领域都得到了广泛的应用。然而,目前统计指数理论仍然不够成熟,统计指数编制方法还十分单一。与其他统计理论的发展形成鲜明对照,统计指数理论发展到今天,似乎与现代数理统计方法渐行渐远。特别是在统计指数编制的实践中,大量的历史信息(先验信息)被弃之不用,造成信息资源浪费,影响了统计指数编制的准确性。为了促进统计指数理论与现代数理统计方法的融合,进一步发展统计指数理论,丰富统计指数编制方法,充分利用…     

冲突、合作与和谐社会——2005年诺贝尔经济学奖得主的学术思想及其启示

因其对于冲突与合作的研究,①罗伯特·奥曼和托马斯·谢林获得了2005年诺贝尔经济学奖。博弈论的研究再次获得诺贝尔经济学奖的认可,是因为它创造了一种全新的思考方式,近年来,博弈论成为广为接受的研究工具。奥曼和谢林对于博弈论的理论拓展和实际运用,增强了世人对冲突与合作的理解,并且,这一研究超越了经济范畴,影响了社会科学多个领域。②他们对于冲突与合作的研究体现了博弈论在互动中寻求均衡的核心理念,其研究成果有助于解决当前我国社会经济转型过程中凸现的问题,对于缓解冲突、引导合作,推动和谐社会③进程有着重要启示。一、奥曼…     

挠性转子动不平衡量的极大似然估计

本文提出利用模态参数识别技术进行挠性转子动平衡的方法。为了计及平衡过程中测试数据的误差,对动不平衡量采用极大似然估计。本文给出计算机模拟的几个实例以论证此种方法,并提出加速收敛的措施。计算结果表明此法效果是鸿意的。     

网上CAI

用好现代先进技术,开展网络建设,是教育信息化的第一步。本文基于这一思想,介绍了网上CAI的设计思路,描述了该系统的功能,以及实现系统所采用的技术措施。     

On distribution-weighted partial least squares with diverging number of highly correlated predictors

Summary.  Because highly correlated data arise from many scientific fields, we investigate parameter estimation in a semiparametric regression model with diverging number of predictors that are highly correlated. For this, we first develop a distribution-weighted least squares estimator that can recover directions in the central subspace, then use the distribution-weighted least squares estimator as a seed vector and project it onto a Krylov space by partial least squares to avoid computing the inverse of the covariance of predictors. Thus, distrbution-weighted partial least squares can handle the cases with high dimensional and highly correlated predictors. Furthermore, we also suggest an iterative algorithm for obtaining a better initial value before implementing partial least squares. For theoretical investigation, we obtain strong consistency and asymptotic normality when the dimension p of predictors is of convergence rate O { n ^1/2/ log ( n )} and o ( n ^1/3) respectively where n is the sample size. When there are no other constraints on the covariance of predictors, the rates n ^1/2 and n ^1/3 are optimal. We also propose a Bayesian information criterion type of criterion to estimate the dimension of the Krylov space in the partial least squares procedure. Illustrative examples with a real data set and comprehensive simulations demonstrate that the method is robust to non-ellipticity and works well even in 'small n –large p ' problems.     

Parallel tempering for dynamic generalized linear models

ABSTRACT

Markov chain Monte Carlo (MCMC) methods can be used for statistical inference. The methods are time-consuming due to time-vary. To resolve these problems, parallel tempering (PT), as a parallel MCMC method, is tried, for dynamic generalized linear models (DGLMs), as well as the several optimal properties of our proposed method. In PT, two or more samples are drawn at the same time, and samples can exchange information with each other. We also present some simulations of the DGLMs in the case and provide two applications of Poisson-type DGLMs in financial research.     

Estimation on semi-functional linear errors-in-variables models

Abstract

Semi-functional linear regression models are important in practice. In this paper, their estimation is discussed when function-valued and real-valued random variables are all measured with additive error. By means of functional principal component analysis and kernel smoothing techniques, the estimators of the slope function and the non parametric component are obtained. To account for errors in variables, deconvolution is involved in the construction of a new class of kernel estimators. The convergence rates of the estimators of the unknown slope function and non parametric component are established under suitable norm and conditions. Simulation studies are conducted to illustrate the finite sample performance of our method.     

Testing the proportional odds model for interval-censored data

This paper discusses the goodness-of-fit test for the proportional odds model for K-sample interval-censored failure time data, which frequently occur in, for example, periodic follow-up survival studies. The proportional odds model has a feature that allows the ratio of two hazard functions to be monotonic and converge to one and provides an important tool for the modeling of survival data. To test the model, a procedure is proposed, which is a generalization of the method given in Dauxois and Kirmani [Dauxois JY, Kirmani SNUA (2003) Biometrika 90:913–922]. The asymptotic distribution of the procedure is established and its properties are evaluated by simulation studies