Learning from a lot: Empirical Bayes for high‐dimensional model‐based prediction

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, stored in public repositories. We review applications of a variety of empirical Bayes methods to several well‐known model‐based prediction methods, including penalized regression, linear discriminant analysis, and Bayesian models with sparse or dense priors. We discuss “formal” empirical Bayes methods that maximize the marginal likelihood but also more informal approaches based on other data summaries. We contrast empirical Bayes to cross‐validation and full Bayes and discuss hybrid approaches. To study the relation between the quality of an empirical Bayes estimator and p, the number of variables, we consider a simple empirical Bayes estimator in a linear model setting. We argue that empirical Bayes is particularly useful when the prior contains multiple parameters, which model a priori information on variables termed “co‐data”. In particular, we present two novel examples that allow for co‐data: first, a Bayesian spike‐and‐slab setting that facilitates inclusion of multiple co‐data sources and types and, second, a hybrid empirical Bayes–full Bayes ridge regression approach for estimation of the posterior predictive interval.     

Estimation of the marginal expected shortfall under asymptotic independence

We study the asymptotic behavior of the marginal expected shortfall when the two random variables are asymptotic independent but positively associated, which is modeled by the so-called tail dependent coefficient. We construct an estimator of the marginal expected shortfall, which is shown to be asymptotically normal. The finite sample performance of the estimator is investigated in a small simulation study. The method is also applied to estimate the expected amount of rainfall at a weather station given that there is a once every 100 years rainfall at another weather station nearby.     

西汉赋家的个体性生命焦虑

个体性生命焦虑是西汉赋家比较浓郁的生命意识。它较集中地体现于骚体赋和拟骚赋中。可以说,西汉赋家继承先秦时代的人文精神,并结合新时代对士人话语自由及人格自由的限制与剥夺,将屈原的楚骚精神进一步发扬光大,对后世文学关注生命具有深远影响。     

Book Reviews

Books reviewed:
M Hollander and D Wolfe, Nonparametric Statistical Methods
T Leonard and J.S.J Hsu, Bayesian Methods     

Measuring agreement between two statistics with applications to age standardization

Summary.  We detail a general method for measuring agreement between two statistics. An application is two ratios of directly standardized rates which differ only by the choice of the standard. If the statistics have a high value for the coefficient of agreement then the expected squared difference between the statistics is small relative to the variance of the average of the two statistics, and inferences vary little by changing statistics. The estimation of a coefficient of agreement between two statistics is not straightforward because there is only one pair of observed values, each statistic calculated from the data. We introduce estimators of the coefficient of agreement for two statistics and discuss their use, especially as applied to functions of standardized rates.     

林业投资均衡性的理论分析

我国林业投资体制的改革面临着许多新的课题,研究市场经济条件下林业投资状况十分必要。首先,从均衡理论出发,在分析宏观经济政策对林业的影响和林业投资现状基础上,对形成这种状况的主要原因进行了探讨;其次,以林业投资对象为主体,对其微观经济行为的成本与收益问题进行了分析;最后,提出深化林业投资体制改革要促进投资主体多元化,给予林业更多的政策扶持,进一步完善林业法律法规,以促进我国林业持续稳定地发展。     

Marginal and association regression models for longitudinal binary data with drop‐outs: A likelihood‐based approach

Longitudinal data often contain missing observations, and it is in general difficult to justify particular missing data mechanisms, whether random or not, that may be hard to distinguish. The authors describe a likelihood‐based approach to estimating both the mean response and association parameters for longitudinal binary data with drop‐outs. They specify marginal and dependence structures as regression models which link the responses to the covariates. They illustrate their approach using a data set from the Waterloo Smoking Prevention Project They also report the results of simulation studies carried out to assess the performance of their technique under various circumstances.     

变革中的高校教师焦虑心理分析

高校教师焦虑心理的存在是目前高校中一种较普遍的现象。教师焦虑心理对提高教学质量和深化教育改革有一定的消极影响,因此,关注其焦虑心理并采取措施降低教师焦虑心理是实现高等教育持续发展的重要内容。     

社会边缘群体对社会稳定的影响及对策--以哈尔滨建筑业农民工为例

社会稳定和社会边缘群体的生存状况紧密相连.建筑业农民工群体是中国社会边缘群体的重要组成部分,必须通过实证研究分析他们的生存状态及其与社会稳定之间的关系.通过抽样方法和问卷调查,从经济状况、社会分配、社会心理和社会控制等四个方面透视哈尔滨市建筑业农民工群体的生活状况,目前还不是影响社会稳定的因素.但从长期来看,若不注重研究并改善其境遇,则可能成为社会稳定的隐患.鉴于此,必须综合利用农民工社会保障制度、工会组织、技能培训、改善食宿和安全条件以及多样化的休闲途径,来保证这一群体的生活质量和合法权益,以维护社会稳定.     

反Fuzzy子群的直积

1990年R.Biswas在[2]中提出了反Fuzzy子群的概念.在此基础上本文相应定义了反Fuzzy子群的直积.接着讨论了其包括正规、共轭情况下的若干性质.此外,还给出了直积μ_1×μ_2是G×G上的反Fuzzy子群的一个充要条件.