关于巩固我国农村地区扶贫成果的若干思考

“九五”期间我国农村地区扶贫开发工作取得了历史性的伟大成就。但应看到 ,从脱贫到实现小康和更为富裕的目标 ,仍有相当长的奋斗历程 ,薄弱的经济基础、脆弱的生态环境、不良的人口状况是影响巩固扶贫成果的主要因素。为此 ,必须认定优化人口状况、持续经济增长和实现可持续发展是巩固扶贫成果的基本途径     

中国共产党三代领导人的人口思想

人口问题始终是和中国社会发展密切相关的重要问题。中国共产党三代领导人把马克思主义人口理论与中国实际相结合 ,形成了各具特色的人口思想。毛泽东的人口思想经历了一个曲折发展的过程 ,但他成功地启动了中国的计划生育事业。邓小平将人口纳入现代化总体发展战略 ,把计划生育作为国家的基本国策确立下来。江泽民把人口问题提到可持续发展战略的首要位置 ,把我们对人口与计划生育工作的认识提高到一个新水平 ,形成了大人口观念。     

铁路发展与近代人口流动

铁路在中国兴建之后,作为一种新式交通工具促进了人口流动。铁路是近代向南北移民的主要交通工具;因铁路之兴建,大批外国侨民移入中国;在救助灾民、难民方面,铁路发挥了重要作用;其自身修筑也吸纳了大量人口,我们要充分肯定铁路在促进人口流动过程中的重要作用。     

构建人口结构安全预警系统初探

人口结构安全的实现将是解决整个人口安全问题的重要基础之一。基于预防预控人口结构安全隐患的现实需要,根据人口学理论和危机管理理论,构建了人口结构安全预警系统的基本框架,其中重点探讨了人口结构预警指标体系、安全阀警戒线的确立,以及模拟评估子系统的建立。     

Stopping-time resampling for sequential Monte Carlo methods

Summary.  Motivated by the statistical inference problem in population genetics, we present a new sequential importance sampling with resampling strategy. The idea of resampling is key to the recent surge of popularity of sequential Monte Carlo methods in the statistics and engin-eering communities, but existing resampling techniques do not work well for coalescent-based inference problems in population genetics. We develop a new method called 'stopping-time resampling', which allows us to compare partially simulated samples at different stages to terminate unpromising partial samples and to multiply promising samples early on. To illustrate the idea, we first apply the new method to approximate the solution of a Dirichlet problem and the likelihood function of a non-Markovian process. Then we focus on its application in population genetics. All our examples show that the new resampling method can significantly improve the computational efficiency of existing sequential importance sampling methods.     

“民工荒”的成因、绩效与对策

围绕近期出现的“民工荒”现象,分析了“民工荒”出现的深层次原因,揭示了“民工荒”的存在对我国目前经济增长与未来经济发展所产生的积极意义和不容忽视的影响,并从有利于农民广泛就业的角度,给出了相应的对策思考。     

西部大开发中人口状况的良性转化

西部大开发为改善西部的人口状况提供了历史性机遇。应在西部大开发的实践中完善人口调控的利益导向机制 ,发展科学教育事业 ,调整经济结构 ,从而实现西部人口数量、素质和结构的良性转化     

对人口老龄化社会经济影响问题研究的回顾与分析

针对目前我国人口老龄化社会经济影响问题研究中的某些误区和概念、理论模糊的问题 ,通过对先前文献的简要回顾 ,从基本概念和理论上分析了这些问题的症结及其原因所在 ,并提出了解决这些问题的基本途径     

Utilizing the Flexibility of the Epsilon-Skew-Normal Distribution for Common Regression Problems

In this paper we illustrate the properties of the epsilon-skew-normal (ESN) distribution with respect to developing more flexible regression models. The ESN model is a simple one-parameter extension of the standard normal model. The additional parameter ~ corresponds to the degree of skewness in the model. In the fitting process we take advantage of relatively new powerful routines that are now available in standard software packages such as SAS. It is illustrated that even if the true underlying error distribution is exactly normal there is no practical loss n power with respect to testing for non-zero regression coefficients. If the true underlying error distribution is slightly skewed, the ESN model is superior in terms of statistical power for tests about the regression coefficient. This model has good asymptotic properties for samples of size n>50.     

Bayesian Computations for Random Environment Models

This paper deals with the analysis of reliability data from a Bayesian perspective for Random Environment (RE) models. We give an overview of current literature on RE models. We also study the computational problems associated with the implementations of RE models in a Bayesian setting. Then, we present the Markov Chain Monte Carlo technique to solve such problems. These problems arise in posterior and predictive analysis and their relevant quantities such as mean, variance, and median. The suggested methodology is incorporated with an illustration.