Estimating household structure in ancient China by using historical data: a latent class analysis of partially missing patterns

Summary.  Social data often contain missing information. The problem is inevitably severe when analysing historical data. Conventionally, researchers analyse complete records only. Listwise deletion not only reduces the effective sample size but also may result in biased estimation, depending on the missingness mechanism. We analyse household types by using population registers from ancient China (618–907 AD) by comparing a simple classification, a latent class model of the complete data and a latent class model of the complete and partially missing data assuming four types of ignorable and non-ignorable missingness mechanisms. The findings show that either a frequency classification or a latent class analysis using the complete records only yielded biased estimates and incorrect conclusions in the presence of partially missing data of a non-ignorable mechanism. Although simply assuming ignorable or non-ignorable missing data produced consistently similarly higher estimates of the proportion of complex households, a specification of the relationship between the latent variable and the degree of missingness by a row effect uniform association model helped to capture the missingness mechanism better and improved the model fit.     

一种求解双目标线性规划的方法及其在上海市土地使用和交通方面的应用

本文介绍了一种求解双目标线性规划(SBLP)的方法.根据上海市土地使用与交通的现状建立了一个拟动态的模型(BOLT),并用该方法加以求解。根据得到的解对上海市土地使用与交通相互作用的情况进行了分析。     

经济全球化影响下的中国计划生育发展趋势

中国的计划生育是在计划经济体制下形成的,其特点多数与经济全球化的规则有着较大的差距。因此,经济全球化和中国加入世贸组织对中国计划生育的影响是全面而深刻的。在经济全球化的影响下,中国计划生育的发展趋势主要体现在六个方面。     

An individual measure of relative survival

Summary.  Relative survival techniques are used to compare survival experience in a study cohort with that expected if background population rates apply. The techniques are especially useful when cause-specific death information is not accurate or not available as they provide a measure of excess mortality in a group of patients with a certain disease. Whereas these methods are based on group comparisons, we present here a transformation approach which instead gives for each individual an outcome measure relative to the appropriate background population. The new outcome measure is easily interpreted and can be analysed by using standard survival analysis techniques. It provides additional information on relative survival and gives new options in regression analysis. For example, one can estimate the proportion of patients who survived longer than a given percentile of the respective general population or compare survival experience of individuals while accounting for the population differences. The regression models for the new outcome measure are different from existing models, thus providing new possibilities in analysing relative survival data. One distinctive feature of our approach is that we adjust for expected survival before modelling. The paper is motivated by a study into the survival of patients after acute myocardial infarction.     

A bayesian estimator for the dependence function of a bivariate extreme‐value distribution

Any continuous bivariate distribution can be expressed in terms of its margins and a unique copula. In the case of extreme‐value distributions, the copula is characterized by a dependence function while each margin depends on three parameters. The authors propose a Bayesian approach for the simultaneous estimation of the dependence function and the parameters defining the margins. They describe a nonparametric model for the dependence function and a reversible jump Markov chain Monte Carlo algorithm for the computation of the Bayesian estimator. They show through simulations that their estimator has a smaller mean integrated squared error than classical nonparametric estimators, especially in small samples. They illustrate their approach on a hydrological data set.     

基于局部社团结构平衡的双模符号网络链路预测研究

随着互联网产业的高速发展,双模符号网络已经成为一类常见的复杂网络,然而针对此 类网络的分析较少。本文在传统非符号网络局部社团理论和符号网络结构平衡理论的基础上,首次提出了双模符号网络下的局部社团理论。这一理论不仅考虑了符号网络中共同邻居的信息,还引入了共同邻居间存在的连接。进一步地,本文推导出符号网络中基于局部社团信息的加权平衡回路增益指数,该指标可以表示双模符号网络中用户节点和产品节点间的符号关系。为了将该指标更好地应用于双模 符号网络链路预测问题,本文提出了加权平衡回路增益分类器算法。实验结果表明,相比其他经典链路预测算法,新算法具有更好的预测能力。     

Coversge probabilty to the original data by prediction intervals in simple linear regression

The coverage rate of the original data by the prediction interval in simple linear regression is obtained by computer simulation. The results show that for small sample size, the coverage rate is higher than the assigned prediction coverage rate (confidence level). The two coverage rates begin to converge when the sample size is larger than 50 and the convergence rate depends very little on the distribution of the independent variable. Also, theoretical results on the asymptotic coverage rate and on the absolute minimum bounds are obtained     

金融市场收益率方向预测模型研究———基于文本大数据方法

金融市场的发展关系着一国的经济命脉,而股票市场作为金融市场的重要组成部分,对其收益率的研究也一直都是学术界的热点。财经新闻常被认为蕴含着丰富的信息,其中所包含的情感信息作为影响投资者投资决策的重要因素之一,对股票收益率也具有一定的影响。故本文构建了适用于金融投资领域的财经新闻情感词典来对财经新闻进行文本分析,同时构造了新的预测模型:将财经新闻文本中所含的情感量化为情绪指数并与时变密度函数相结合,得到时变加权密度模型。并在此基础上以模型评分为权重组合多个预测模型构建出评分加权模型用于股票收益率预测。结果显示,加入情绪指数能有效提高模型预测能力,而评分加权模型的预测能力则在此基础上更进一步,在准确率以及评分规则上基本达到双重最优。     

岩石可钻性能量法现场实验研究

本文介绍了岩石可钻性能全法在油田现场实脸研究的成果:确定其可钻性指标凡对地层的适用范围，证明K指标比其他可钻性指标能更容易、史好地反映出井下实际地层可钻性变化情无，用K指标预浏钻速与实际钻速接近.     

中国人口学科国际化水平及其影响因素

国际化是学科成熟与发展的一个重要指标。但是作为世界人口第一大国,中国人口学科的国际化并没有发展到一个相对应的水平。在界定了学科国际化概念的基础上,借助问卷调查数据来分析中国人口学科国际化的现状,探讨中国人口科学继续与国际学界融合所面临的困难及其主要原因。结果表明,中国人口学的国际化明显处于不断萎缩的态势,其直接动因和深层次缘由分别是整个人口学界的国际化意识与能力的减弱,以及人口学科文化与制度本身存在的缺陷。加强国际化的学科文化建设与建立相配套的学科制度是提高中国人口学科国际化水平的重要途径。