On Using Linear Regressions in Welfare Economics

This article consists of two parts. The first part shows that the ordinary least squares regression coefficient is a weighted average of slopes between adjacent sample points. When applied to a linear regression, with income as the independent variable, the regression coefficient depends heavily on the slopes of high-income groups. The weight of the highest income decile may well exceed that of the other nine deciles. This may be undesirable, especially if the regression is used for welfare analysis, because the marginal propensities to consume attributed to the commodities are determined by the high-income groups. The second part of the article proposes alternative estimators, the extended Gini estimators, that enable investigators to control the weighting scheme and to incorporate their social views into the weighting scheme of the estimators     

Bayes designs for multiple linear regression on the unit sphere

We deal with experimental designs minimizing the mean square error of the linear BAYES estimator for the parameter vector of a multiple linear regression model where the experimental region is the k-dimensional unit sphere. After computing the uniquely determined optimum information matrix, we construct, separately for the homogeneous and the inhomogeneous model, both approximate and exact designs having such an information matrix.     

基于白化权函数的区间灰数关联度模型

根据区间灰数空间映射思想,引入白化权函数来表征区间灰数的分布信息。定义灰形和灰心分别来描述白化权函数与区间灰数围成的封闭几何图形及其几何重心;定义灰圆和灰径分别来表示以灰心为圆心且与灰形具有相同面积的标准圆及其半径。在此基础上,以灰心序列的横、纵坐标序列为对象,以灰径的离差为权重,依照邓氏关联度原理构造了一个基于白化权函数的区间灰数关联度模型。并针对一种最为典型的白化权函数,具体导出了区间灰数关联度的计算公式。最后,通过一个供应商选择的实例验证了模型的科学性和可行性。基于白化权函数的区间灰数关联度在资源勘探、机器故障诊断、产品品质评价及供应商选择等方面有着广泛的应用前景。     

Inhomogeneous Markov Chains and Ergodicity Coefficients: John Hajnal (1924–2008)

In 1958, a paper by John Hajnal, a demographer and mathematical statistician, was fundamental in the revival of the theory of inhomogeneous Markov chains. Hajnal made his contribution by the development of tools for the analysis of weak ergodicity, and proofs of fundamental theorems. This article reviews Hajnal's career, and then focuses on the four topics: 1. ergodicity coefficients and the weak ergodicity theorem; 2. scrambling matrices; 3. the coupling theorem; and 4. non-negative matrix products. Related work by other authors, especially Wolfgang Doeblin, is mentioned in context. Attention is given to some recent surveys and applications of ergodicity coefficients, including the Google matrix.     

灰色关联决策方法研究

以灰色决策分析理论为基础,探讨了经典灰色关联决策方法的优势和不足。提出了基于理想方案的最大关联度方法、基于临界方案的最小关联度方法,以及同时考虑理想方案和临界方案的综合关联度方法及其相关概念。建立了灰色区间关联系数公式和灰色区间相对关联系数公式。运用分析技巧,构建了上述3种关联度决策算法。指出了灰色区间关联系数公式和最大关联度方法分别是经典灰色关联系数公式和灰色关联决策方法的推广,而最小关联度方法和综合关联度方法是经典灰色关联决策方法的拓展。文中实例说明了所提出的灰色关联决策方法的合理性及其算法的有效性。     

医学生与非医学生性行为现状差异比较

目的:比较近十年中国大学的医学生与非医学生在性行为的发生率和保护率上的差异,探讨医学教育对性行为现状的影响,为更好地开展大学生性教育提供依据.方法:收集2002年1月至2012年1月国内发表的关于医学生与非医学生性行为现状的文献,按照纳入剔除标准进行筛选、评价,并提取数据进行荟萃分析.若异质性过于明显,无法解决时,则放弃Meta分析法,只对结果进行一般的统计描述.结果:符合要求的文献共15篇,提取数据15组.异质性过于明显而无法解决,故进行一般统计描述.医学生的性行为发生率低于非医学生,性行为的保护率高于非医学生;不论医学生还是非医学生,性行为的发生率与保护率均有逐年上升的趋势.结论:高校大学生性行为问题不容乐观,急需干预措施.     

一种新的灰色绝对关联度模型及其应用

为了处理序列曲线间的负相关等问题,并使关联满足一定的性质,基于灰色关联分析的基本思想,本文利用数列曲线的平均相对变化态势构建了一种新的灰色绝对关联度模型,并探讨了模型的唯一性、对称性、相似性、平行性、一致性等性质,而后以新模型对我国及各省市区产业结构的有序度进行了测算,结果表明新模型计算简单,计算量小,更与实际相符。     

Intrinsically Dynamic Multistate Models

Multistate life table models, which follow persons through more than one living state, have found increasing use in demographic analyses. Multistate stable populations, however, are infrequently used because the constant rate assumption is quite strong and such populations can take centuries to approach stability. Dynamic models, that is models where the rates can change over time, are examined to derive a new solution for the size and composition of a multistate population in terms of the sequence of underlying population projection matrices (PPMs). Constraints on the subordinate eigenvalues and the subordinate eigenvectors of the time-varying PPMs produce a model population that grows according to the dominant eigenvalues of each time-specific PPM and has a state composition that depends only on the most recent PPM. The two living state model is examined in detail, relationships between the PPM elements and the size and composition of the model are explored, and two illustrative applications of the model are presented.