Religiosity and the political economy of the Salem witch trials

Salem Village, both before and through the witchcraft trials, was a religion-based community, allowing its minister to exert a level of political–economic control over its citizens. During the height of the witchcraft episode, there was an increased demand for ministerial services (salvation) in the Salem area. Recent research has argued that the minister used the witchcraft episode to maintain and build upon personal and corporate wealth. In the years after the witchcraft trials changes were made in the business and legal environment of the surrounding New England region. By transitioning to a more neutral rules system with a larger area of consensus for the system, Salem and the rest of the New England transitioned from the 17th Century traditional, religion-based community to a more rules-based, pro-business one in the 18th Century.     

地区间个人收入差距的状况及特点(英文)

在地区收入差距的文献中,一直缺乏从个人收入角度出发的研究;而关于个人收入分配的研究,也很少考察地区差异。文章使用2005年全国1％人口普查数据,从个人收入角度描述了全国及（几种不同定义下的）地区间的个人收入差距,并分析了影响个人收入差距的因素,得到了一些有意义的结果。     

南宋江南市场的移民因素

大规模移民与劳动力流动及其所带动的其他生产要素与商品的流动和组合,在江南市场实现资源配置.移民的技能、资本在城镇进入劳动力市场与工商服务业,在农村进入土地交易与租佃市场,移民的多样化消费需求与开拓意识,都促进了江南各类市场的发展.临安大都会市场是移民因素最集中和深刻的体现,江南市镇在南宋的成长,亦广泛地烙下移民的印迹.     

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.     

Profile information matrix for nonlinear transformation models

For semiparametric models, interval estimation and hypothesis testing based on the information matrix for the full model is a challenge because of potentially unlimited dimension. Use of the profile information matrix for a small set of parameters of interest is an appealing alternative. Existing approaches for the estimation of the profile information matrix are either subject to the curse of dimensionality, or are ad-hoc and approximate and can be unstable and numerically inefficient. We propose a numerically stable and efficient algorithm that delivers an exact observed profile information matrix for regression coefficients for the class of Nonlinear Transformation Models [A. Tsodikov (2003) J R Statist Soc Ser B 65:759-774]. The algorithm deals with the curse of dimensionality and requires neither large matrix inverses nor explicit expressions for the profile surface.     

Statistical consulting at German universities: Results of a survey

The article presents the results of a survey on statistical consulting at German universities, where the survey focused on obtaining information on when, where and to whom statistical consulting is provided. We investigate the financial frame of the activity and question the advantages and disadvantages from a consultant’s point of view.     

Statistical consulting

The paper and the special issue focus on the activity of statistical consulting and its varieties. This includes academic consulting, consulting to and in industry as well as statistics in public media.     

Three-level main-effects designs exploiting prior information about model uncertainty

To explore the projection efficiency of a design, Tsai, et al [2000. Projective three-level main effects designs robust to model uncertainty. Biometrika 87, 467–475] introduced the Q criterion to compare three-level main-effects designs for quantitative factors that allow the consideration of interactions in addition to main effects. In this paper, we extend their method and focus on the case in which experimenters have some prior knowledge, in advance of running the experiment, about the probabilities of effects being non-negligible. A criterion which incorporates experimenters’ prior beliefs about the importance of each effect is introduced to compare orthogonal, or nearly orthogonal, main effects designs with robustness to interactions as a secondary consideration. We show that this criterion, exploiting prior information about model uncertainty, can lead to more appropriate designs reflecting experimenters’ prior beliefs.     

Optimality and bias of some interpolation and extrapolation designs

We consider interpolation and extrapolation designs with controlled bias. A consistent estimate of an upper bound of the bias is presented. The estimate of some extrapolated value is obtained in a two-stage procedure. The first one provides an estimate of some interpolated value. The second one uses a Taylor expansion around this point. This procedure yields a new type of designs. We discuss their optimality properties with respect to the variance and the bias.