Bayesian analysis of directed graphs data with applications to social networks

Summary.  A fully Bayesian analysis of directed graphs, with particular emphasis on applica- tions in social networks, is explored. The model is capable of incorporating the effects of covariates, within and between block ties and multiple responses. Inference is straightforward by using software that is based on Markov chain Monte Carlo methods. Examples are provided which highlight the variety of data sets that can be entertained and the ease with which they can be analysed.     

盆景风格因子初探

盆景艺术风格是盆景艺术家的创作个性在作品中的外在表现 ,它对盆景艺术的发展起着很重要的作用 ,人们对盆景的感性认识直接来源于盆景的风格。大部分盆景方面的书和文章都会涉及到盆景艺术风格的问题 ,但是 ,迄今为止对盆景艺术风格的形成和发展进行过系统研究的人还不是很多。基于对艺术发展规律和中国各种艺术风格盆景发展历史的研究 ,该文详细论述了影响盆景艺术风格形成和发展的内在、外在因素及它们之间的关系 ,并对怎样给我国盆景艺术注入新的活力提出了一些建议 ,对我国盆景艺术的发展和创新起到一定的指导作用     

D-efficient window experimental designs

In the paper we present a new method of calculating sampling intervals, so-called windows, allowing an experimenter some flexibility in timing the sample collection, while a minimum required design efficiency for parameter estimation is assured. The method is based on the Equivalence Theorem for D-optimality what makes the length of each window related to the parameter sensitivities. An example of calculating the windows in a pharmacokinetic study is presented. Some other methods of calculating efficient sampling windows are briefly discussed.     

Adaptive Management: A Paradigm for Remediation of Public Facilities Following a Terrorist Attack

Terrorist actions are aimed at maximizing harm (health, psychological, economical, and political) through the combined physical impacts of the act and fear. Immediate and effective response to a terrorist act is critical to limit human and environmental harm, effectively restore facility function, and maintain public confidence. Though there have been terrorist attacks in public facilities that we have learned from, overall our experiences in restoration of public facilities following a terrorist attack are limited. Restoration of public facilities following a release of a hazardous material is inherently far more complex than in industrial settings and has many unique technical, economic, social, and political challenges. For example, there may be a great need to quickly restore the facility to full operation and allow public access even though it was not designed for easy or rapid restoration, and critical information is needed for quantitative risk assessment and effective restoration must be anticipated to be incomplete and uncertain. Whereas present planning documents have substantial linearity in their organization, the “adaptive management” paradigm provides a constructive parallel paradigm for restoration of public facilities that anticipates and plans for uncertainty, inefficiencies, and stakeholder participation. Adaptive management grew out of the need to manage and restore natural resources in highly complex and changing environments with limited knowledge about causal relationships and responses to restoration actions. Similarities between natural resource management and restoration of a public facility after a terrorist attack suggest that integration of adaptive management principles explicitly into restoration processes will result in substantially enhanced and flexible responses necessary to meet the uncertainties of potential terrorist attacks.     

Model Diagnostics for Remote Access Regression Servers

To protect public-use microdata, one approach is not to allow users access to the microdata. Instead, users submit analyses to a remote computer that reports back basic output from the fitted model, such as coefficients and standard errors. To be most useful, this remote server also should provide some way for users to check the fit of their models, without disclosing actual data values. This paper discusses regression diagnostics for remote servers. The proposal is to release synthetic diagnostics—i.e. simulated values of residuals and dependent and independent variables–constructed to mimic the relationships among the real-data residuals and independent variables. Using simulations, it is shown that the proposed synthetic diagnostics can reveal model inadequacies without substantial increase in the risk of disclosures. This approach also can be used to develop remote server diagnostics for generalized linear models.     

经济系统的演化与政策作用

该文根据耗散结构的基本原理 ,将经济系统划分为平衡态、过渡态和自组织状态。并将政策因素看成是一种外部调控手段 ,分析了在经济系统的不同状态下 ,政策因素对改变系统的结构及变化趋势所起的不同作用     

法国会计模式的分析及对中国的借鉴

该文分析了法国会计模式的特点和影响因素 ,认为法国会计模式与中国会计模式存在相似之处 ,并借鉴法国 1 996年以来会计改革的经验 ,对完善我国会计模式提出了建议     

Mission,money, and merit: Strategic decision making by nonprofit managers

Public and nonprofit organizations need to make strategic choices about where to invest their resources. They also need to expose hidden managerial assumptions and lack of adequate knowledge that prevent the attainment of consensus in strategic decision making. The approach we developed and tested in the field used a dynamic, three‐dimensional model that tracks individual programs in an organization's portfolio on their contribution to mission, money, and merit. The first dimension measures whether the organization is doing the right things; the second, whether it is doing things right financially; and the third, whether it doing things right in terms of quality. Senior managers provide their own evaluations of the organization's programs. Both the consensus view and the variation in individual assessments contribute to an improved managerial understanding of the organization's current situation and to richer discussions in strategic decision making. In field tests, this visual model proved to be a useful and powerful tool for illuminating underlying assumptions and variations in knowledge among managers facing the complex, multidimensional tradeoffs needed in strategic decision making.     

Data skeletons: simultaneous estimation of multiple quantiles for massive streaming datasets with applications to density estimation

We consider the problem of density estimation when the data is in the form of a continuous stream with no fixed length. In this setting, implementations of the usual methods of density estimation such as kernel density estimation are problematic. We propose a method of density estimation for massive datasets that is based upon taking the derivative of a smooth curve that has been fit through a set of quantile estimates. To achieve this, a low-storage, single-pass, sequential method is proposed for simultaneous estimation of multiple quantiles for massive datasets that form the basis of this method of density estimation. For comparison, we also consider a sequential kernel density estimator. The proposed methods are shown through simulation study to perform well and to have several distinct advantages over existing methods.