道德理想与世俗规范的交融--关于遗失物拾得立法的几点思考

在市场经济带来的观念转型大背景下,我国物权立法中关于遗失物拾得的规定方式,存在着实现道德理想的愿望与世俗利益需求的价值冲突。从冲突走向交融是遗失物拾得立法过程的基本走向。必须导入现代民法理念,将法律规范与道德规范区别开,并进一步分析法律如何寻找道德与利益的平衡点。     

陕西省出生人口性别比定量分析与对策探讨

文章根据陕西省历次人口普查、部分人口抽样调查资料及公安、教育、计生统计报表数据，时全省出生人口性别失衡程度、女婴缺失数量和分因素贡献率等几个问题进行定量分析，并对出生人口性别比综合治理和科学决策提出建议。     

Designing and integrating composite networks for monitoring multivariate gaussian pollution fields

Networks of ambient monitoring stations are used to monitor environmental pollution fields such as those for acid rain and air pollution. Such stations provide regular measurements of pollutant concentrations. The networks are established for a variety of purposes at various times so often several stations measuring different subsets of pollutant concentrations can be found in compact geographical regions. The problem of statistically combining these disparate information sources into a single 'network' then arises. Capitalizing on the efficiencies so achieved can then lead to the secondary problem of extending this network. The subject of this paper is a set of 31 air pollution monitoring stations in southern Ontario. Each of these regularly measures a particular subset of ionic sulphate, sulphite, nitrite and ozone. However, this subset varies from station to station. For example only two stations measure all four. Some measure just one. We describe a Bayesian framework for integrating the measurements of these stations to yield a spatial predictive distribution for unmonitored sites and unmeasured concentrations at existing stations. Furthermore we show how this network can be extended by using an entropy maximization criterion. The methods assume that the multivariate response field being measured has a joint Gaussian distribution conditional on its mean and covariance function. A conjugate prior is used for these parameters, some of its hyperparameters being fitted empirically.     

Estimation in capture–recapture models when covariates are subject to measurement errors and missing data

For capture–recapture models when covariates are subject to measurement errors and missing data, a set of estimating equations is constructed to estimate population size and relevant parameters. These estimating equations can be solved by an algorithm similar to the EM algorithm. The proposed method is also applicable to the situation when covariates with no measurement errors have missing data. Simulation studies are used to assess the performance of the proposed estimator. The estimator is also applied to a capture–recapture experiment on the bird species Prinia flaviventris in Hong Kong. The Canadian Journal of Statistics 37: 645–658; 2009 © 2009 Statistical Society of Canada     

Assessing robustness of crossover designsto subjects dropping out

In some crossover experiments, particularly in medical applications, subjects may fail to complete their sequences of treatments for reasons unconnected with the treatments received. A method is described of assessing the robustness of a planned crossover design, with more than two periods, to subjects leaving the study prematurely. The method involves computing measures of efficiency for every possible design that can result, and is therefore very computationally intensive. Summaries of these measures are used to choose between competing designs. The computational problem is reduced to a manageable size by a software implementation of Polya theory. The method is applied to comparing designs for crossover studies involving four treatments and four periods. Designs are identified that are more robust to subjects dropping out in the final period than those currently favoured in medical and clinical trials.     

Missing siblings: seeking more adequate social responses

Little is known about the experience of family and friends when a young adult goes missing, less is known about how siblings make sense of the experience. Police assistance to locate the missing person may be sought but there is little recognition of going missing or missingness as a social issue, and there is little or no adequate social response to the needs of those left behind. This paper links knowledge of siblings, loss and grief to an understanding of this phenomenon. It presents the methodology and findings of an exploratory, qualitative study into the experiences of nine adult siblings of long-term missing people in Australia and presents the themes drawn from their accounts. The themes are briefly elaborated using direct quotations from participants in the study and represented in a diagram. The paper seeks to develop greater understanding of the inter-relationship between missingness and other social issues, to give voice to the views of participants and to encourage practitioners to engage more purposefully in work with family and friends affected by this issue. Some implications for social work practice are presented.     

Estimation of regression models with equi-correlated responses when some observations on the response variable are missing

The present article deals with the problem of estimation of parameters in a linear regression model when some data on response variable is missing and the responses are equi-correlated. The ordinary least squares and optimal homogeneous predictors are employed to find the imputed values of missing observations. Their efficiency properties are analyzed using the small disturbances asymptotic theory. The estimation of regression coefficients using these imputed values is also considered and a comparison of estimators is presented.     

韩国本《十抄诗》中的唐人佚诗辑考

域外汉籍文献对我国学术研究有着重要的参考价值。韩国唐诗选本《十抄诗》,其中包含大量中晚唐佚诗 ,对唐诗研究具有重要意义。这些珍贵材料迄今尚未披露 ,现将其辑为一篇 ,校勘异文 ,并进行了初步的考证     

Nonlinear mixed‐effect models with nonignorably missing covariates

Nonlinear mixed‐effect models are often used in the analysis of longitudinal data. However, it sometimes happens that missing values for some of the model covariates are not purely random. Motivated by an application to HTV viral dynamics, where this situation occurs, the author considers likelihood inference for this type of problem. His approach involves a Monte Carlo EM algorithm, along with a Gibbs sampler and rejection/importance sampling methods. A concrete application is provided.