Mixed estimation of old‐age mortality

The estimation of the mortality of the “oldest old”; is subject to considerable random error, but important prior information exists that can be used to make the estimates more robust. Mixed estimation is a method of incorporating auxiliary information into the statistical estimation of linear models. We extend the method to cover general maximum likelihood estimation, and show that the mixed estimator can be represented approximately as a weighted average of the purely data based estimator and the auxiliary estimator. The methods can be applied to the analysis of the old‐age mortality via logistic and Poisson regression. A major advantage of the mixed estimator is the simplicity with which it can incorporate partial prior information. Moreover, no special software is needed in the fitting. We show how the targeting methods of Coale and Kisker can be represented as mixed estimation in a natural way that is more flexible than the original proposal. We also derive empirical estimates of the target information based on pooled data from several countries with high quality data. We consider the mortality of Finland at ages 80 +, study the reliability of the evidence of mortality crossover, and derive estimates of life expectancy at age 100.     

Boundary-Spanning Demands,Personal Mastery,and Family Satisfaction: Individual and Crossover Effects Among Dual-Earner Parents

Grounded in ecological systems theory, this study modeled family satisfaction as a function of family-unfriendly work culture, work–family blurring, and personal mastery, examining both individual crossover effects. Analysis of data from 273 married dual-earner parents revealed that family-unfriendly work culture was negatively related to family satisfaction, whereas personal mastery was positively related to family satisfaction. Mothers' family-unfriendly work culture and work–family blurring were negatively related to their husbands' family satisfaction, but no parallel crossover findings were obtained for fathers, suggesting gender differences in crossover. Results were consistent with the notion that family life can be compromised by work cultures that create demands spanning both work and family domains. Implications for the management of work and family boundaries are discussed.     

从跨界设计的实例看创造思维的结晶

现代的任何一个领域都不是一项单一的专业所能够独立完成的,它需要跨专业的探索,因而人们越来越多的以多重身份在不同领域穿梭游走,跨界现象便出现了。它既是一种古典工作方式的复兴,也是一种新趋势的融合,强调不同领域事物的“合作、交叉”。今天的跨界已经直指各专业领域的每一处。使得原本互不相关的元素互相交汇融合,成为新的文化符号。     

医工信交叉融合推动高校医学学科发展的思考

生物医学工程专业包含很多方向, 目前很多课程还有待完善, 这在一定程度上制约了中国医工交叉类一流人才培养。从医工交叉型思维方式训练、对国外优质课程进行吸收与重构、\     

Nonparametric approaches for comparing three-period,two-treatment,four-sequence crossover designs

The paper describes nonparametric approaches for comparing three-period, two-treatment, four-sequence crossover designs through testing the hypothesis that the treatments are interchangeable. The proposed approaches are based on a model which incorporates, along with the direct treatment effects, self and mixed carryover effects. Related asymptotic results are obtained. Comparisons among the designs are made numerically with respect to type I error rate and power of the tests considering compound symmetry and autoregressive covariance structures of the response variables. Lengths of the confidence intervals of the treatment differences are also used to make comparative study among the designs.     

证券市场分形结构与市场模型研究——国家自然科学基金项目（70371062）回溯

回顾了国家自然科学基金项目"证券市场分形结构与市场模型研究",70371062,的立项背景,介绍了项目研究的内容、主要研究成果及代表性文献,列举了项目研究所产生的社会影响及下一步的研究设想.     

遗传算法在模糊控制规则优化中的实现

介绍了遗传算法的基本原理及实现步骤,结合气调温度模糊控制器的实例,讨论了其在模糊控制规则优化中的实现,即遗传编码、交叉运算和变异运算。该优化算法为模糊控制器的设计提供了一个正规的可遵循的方法。     

二元判决图变量排序新方法

从遗传算法入手,利用已有的几种启发式变量排序方法的结果作为最初的染色体群体,并适当加入随机变量顺序,然后按照遗传算法的方法进行运算,经过多代循环找到近似最优解。实验结果表明,该方法比已有的启发式方法更有效,能够在全局范围内搜索最优解,对BDD的变量编序和遗传算法的运用具有参考价值。     

An objective Bayesian estimation in a two-period crossover design

Two-period crossover design is one of the commonly used designs in clinical trials. But, the estimation of treatment effect is complicated by the possible presence of carryover effect. It is known that ignoring the carryover effect when it exists can lead to poor estimates of the treatment effect. The classical approach by Grizzle (1965 Grizzle, J.E. (1965). The two-period change-over design and its use in clinical trials. Biometrics 21:467–480. See Grizzle (1974) for corrections.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) consists of two stages. First, a preliminary test is conducted on carryover effect. If the carryover effect is significant, analysis is based only on data from period one; otherwise, analysis is based on data from both periods. A Bayesian approach with improper priors was proposed by Grieve (1985 Grieve, A.P. (1985). A Bayesian analysis of the two-period crossover design for clinical trials. Biometrics 41:979–990.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) which uses a mixture of two models: a model with carryover effect and another without. The indeterminacy of the Bayes factor due to the arbitrary constant in the improper prior was addressed by assigning a minimally discriminatory value to the constant. In this article, we present an objective Bayesian estimation approach to the two-period crossover design which is also based on a mixture model, but using the commonly recommended Zellner–Siow g-prior. We provide simulation studies and a real data example and compare the numerical results with Grizzle (1965 Grizzle, J.E. (1965). The two-period change-over design and its use in clinical trials. Biometrics 21:467–480. See Grizzle (1974) for corrections.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar])’s and Grieve (1985 Grieve, A.P. (1985). A Bayesian analysis of the two-period crossover design for clinical trials. Biometrics 41:979–990.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar])’s approaches.