Modified and Restricted r-k Class Estimators

In this article, we introduce the modified r-k class estimator and the restricted r-k class estimator. We compare the performances of the new estimators to the r-k class estimator with respect to the matrix mean square error (MSE) criterion. As a special case of the restricted r-k class estimator, we obtain the restricted principal components regression (RPCR) estimator. Finally, we conduct a Monte Carlo simulation study and a numerical example to investigate the performances of the proposed estimators by the scalar mean square error (mse) criterion.     

Collaboration in genocide: the Ottoman Empire 1915–1916, the German-occupied Baltic 1941–1944, and Rwanda 1994

This article develops a new paradigm for the study of collaboration by applying the concept to events outside the context of the Second World War. The authors examine three instances of collaboration in twentieth-century mass killings, seeking to situate them within the framework of genocide. Using a multidisciplinary approach, the article questions the validity of explanations of conflict predicated on the existence of binary systems—explanations that appear frequently in comparative genocide studies. The authors relate the decision to participate in mass murder to the history of structural inequality within a given society. The article concludes that, however vague, the concept of collaboration is useful in accentuating a bottom-up approach in the study of genocide.     

LEADING WITH(OUT) SACRIFICE? A PUBLIC‐GOODS EXPERIMENT WITH A PRIVILEGED PLAYER

We analyze two team settings in which one member in a team has stronger incentives to contribute than the others. If contributions constitute a sacrifice for the strong player, the other team members are more inclined to cooperate than if contributions are strictly dominant for the strong player. (JEL C91, C92, H40, H41)     

GIM and logistics in the factory of the future

Abstract

In the future, the competitive strength of industry will depend on its ability to realize flexible production systems, to install intelligent EDP-systems and to link them to a goal-orientated logistic system. Currently, a lot of new strategies, concepts and approaches for production arc being promoted and discussed, often in a spirit of controversy: CIM (computer integrated manufacturing), 'production logistics’, and JIT (just-in-time production) have become familiar concepts which have one thing in common: new structures in production will be necessary. However, the overall effect of CIM is often very small in comparison to the investment for realizing this concept. The main reason is that such projects are missing a logistic orientation. A continuous flow of information and material as envisaged by the logistics principle requires not only that all automation components can be integrated on the technical level, but also that all relevant functions and sectors can be integrated organizationally.     

工程科技创新的人才培养模式研究——澳大利亚查尔斯特大学的启示

工程科技是改变世界重要力量。我国高校工科人才培养是高等教育的重要组成部分,肩负着为国家重大工程科技攻关培养建设者和接班人的重任。在全球范围内,随着新一轮科技革命和产业变革加速演进,以人工智能、大数据为代表的新一代信息技术的快速发展,正在对传统工程教育的人才培养理念、课程设计和教学模式产生革命性影响。工程教育改革已成为高等学校教育改革的热点,各国纷纷出台政策文件以适应现代化工程科技创新对人才培养的需求。文章采用结构化案例,通过分析全球工程教育“新兴领导者”澳大利亚查尔斯特大学工程本科生的培养理念、课程设计和教学模式,为面向工程科技创新的我国高等学校工程人才培养提供了参考。比如要重视产学研资源汇聚,探索服务区域经济发展新模式;构建“工程知识三角”嵌入联动机制,实现创新型工程人才培养;开发多维度教育资源,创设开放融合的“线上+线下”学习生态圈;强化跨学科平台会聚,连接不同学习场景促进工程知识融通。文章为提出面向新时代我国工程科技创新的工程教育改革和人才培养模式提供了借鉴。      

Rubbery Polya Tree

Abstract. Polya trees (PT) are random probability measures which can assign probability 1 to the set of continuous distributions for certain specifications of the hyperparameters. This feature distinguishes the PT from the popular Dirichlet process (DP) model which assigns probability 1 to the set of discrete distributions. However, the PT is not nearly as widely used as the DP prior. Probably the main reason is an awkward dependence of posterior inference on the choice of the partitioning subsets in the definition of the PT. We propose a generalization of the PT prior that mitigates this undesirable dependence on the partition structure, by allowing the branching probabilities to be dependent within the same level. The proposed new process is not a PT anymore. However, it is still a tail‐free process and many of the prior properties remain the same as those for the PT.     

Biases and Uncertainty in Climate Projections

Abstract. We study statistical procedures to quantify uncertainty in multivariate climate projections based on several deterministic climate models. We introduce two different assumptions – called constant bias and constant relation respectively – for extrapolating the substantial additive and multiplicative biases present during the control period to the scenario period. There are also strong indications that the biases in the scenario period are different from the extrapolations from the control period. Including such changes in the statistical models leads to an identifiability problem that we solve in a frequentist analysis using a zero sum side condition and in a Bayesian analysis using informative priors. The Bayesian analysis provides estimates of the uncertainty in the parameter estimates and takes this uncertainty into account for the predictive distributions. We illustrate the method by analysing projections of seasonal temperature and precipitation in the Alpine region from five regional climate models in the PRUDENCE project.     

Estimation for High‐Dimensional Linear Mixed‐Effects Models Using ℓ1‐Penalization

Abstract. We propose an ?₁‐penalized estimation procedure for high‐dimensional linear mixed‐effects models. The models are useful whenever there is a grouping structure among high‐dimensional observations, that is, for clustered data. We prove a consistency and an oracle optimality result and we develop an algorithm with provable numerical convergence. Furthermore, we demonstrate the performance of the method on simulated and a real high‐dimensional data set.     

r − k Class estimator in the linear regression model with correlated errors

Autocorrelation in errors and multicollinearity among the regressors are serious problems in regression analysis. The aim of this paper is to examine multicollinearity and autocorrelation problems concurrently and to compare the r ? k class estimator to the generalized least squares estimator, the principal components regression estimator and the ridge regression estimator by the scalar and matrix mean square error criteria in the linear regression model with correlated errors.     

Problematic concepts,ambivalent identities: Western identity seen from the Otherland

The article attempts to deconstruct the historical construct of ‘The West’ from the perspective of the Otherland and demystify ‘West/Orient’ dichotomy. The dichotomy, the author contends, originated primarily, albeit not exclusively, in the struggle between monotheistic religions and reproduced itself to date even during the stretches of time when it was overshadowed by other political exigencies. It is, however, especially at crucial times like the present when Europe is undergoing significant changes, that such fictions’ supporting a restless, albeit hegemonic, psychic ‘ensemble ‘, have to be subjected to a ‘deconstruction’ process.