An Additive–Multiplicative Restricted Mean Residual Life Model

The mean residual life measures the expected remaining life of a subject who has survived up to a particular time. When survival time distribution is highly skewed or heavy tailed, the restricted mean residual life must be considered. In this paper, we propose an additive–multiplicative restricted mean residual life model to study the association between the restricted mean residual life function and potential regression covariates in the presence of right censoring. This model extends the proportional mean residual life model using an additive model as its covariate dependent baseline. For the suggested model, some covariate effects are allowed to be time‐varying. To estimate the model parameters, martingale estimating equations are developed, and the large sample properties of the resulting estimators are established. In addition, to assess the adequacy of the model, we investigate a goodness of fit test that is asymptotically justified. The proposed methodology is evaluated via simulation studies and further applied to a kidney cancer data set collected from a clinical trial.     

On the Estimation of the Density of a Directional Data Stream

Many directional data such as wind directions can be collected extremely easily so that experiments typically yield a huge number of data points that are sequentially collected. To deal with such big data, the traditional nonparametric techniques rapidly require a lot of time to be computed and therefore become useless in practice if real time or online forecasts are expected. In this paper, we propose a recursive kernel density estimator for directional data which (i) can be updated extremely easily when a new set of observations is available and (ii) keeps asymptotically the nice features of the traditional kernel density estimator. Our methodology is based on Robbins–Monro stochastic approximations ideas. We show that our estimator outperforms the traditional techniques in terms of computational time while being extremely competitive in terms of efficiency with respect to its competitors in the sequential context considered here. We obtain expressions for its asymptotic bias and variance together with an almost sure convergence rate and an asymptotic normality result. Our technique is illustrated on a wind dataset collected in Spain. A Monte‐Carlo study confirms the nice properties of our recursive estimator with respect to its non‐recursive counterpart.     

An Integrated Risk Assessment Model of Township‐Scaled Land Subsidence Based on an Evidential Reasoning Algorithm and Fuzzy Set Theory

Land subsidence risk assessment (LSRA) is a multi‐attribute decision analysis (MADA) problem and is often characterized by both quantitative and qualitative attributes with various types of uncertainty. Therefore, the problem needs to be modeled and analyzed using methods that can handle uncertainty. In this article, we propose an integrated assessment model based on the evidential reasoning (ER) algorithm and fuzzy set theory. The assessment model is structured as a hierarchical framework that regards land subsidence risk as a composite of two key factors: hazard and vulnerability. These factors can be described by a set of basic indicators defined by assessment grades with attributes for transforming both numerical data and subjective judgments into a belief structure. The factor‐level attributes of hazard and vulnerability are combined using the ER algorithm, which is based on the information from a belief structure calculated by the Dempster‐Shafer (D‐S) theory, and a distributed fuzzy belief structure calculated by fuzzy set theory. The results from the combined algorithms yield distributed assessment grade matrices. The application of the model to the Xixi‐Chengnan area, China, illustrates its usefulness and validity for LSRA. The model utilizes a combination of all types of evidence, including all assessment information—quantitative or qualitative, complete or incomplete, and precise or imprecise—to provide assessment grades that define risk assessment on the basis of hazard and vulnerability. The results will enable risk managers to apply different risk prevention measures and mitigation planning based on the calculated risk states.     

The relationship of intimate partner aggression to head injury, executive functioning, and intelligence

Measures of head injury, executive functioning, and intelligence were given to a community sample composed of 102 male perpetrators of intimate partner aggression (IPA) and 62 nonaggressive men. A history of head injury and lower mean score on a measure of verbal intelligence were associated with the frequency of male-perpetrated physical IPA as reported by male perpetrators and their female partners. Lower mean scores on a measure of verbal intelligence also predicted frequency of psychological IPA perpetration. Using the perpetrator subtypes outlined by Holtzworth-Munroe et al. (2000), analyses revealed that compared with other groups, the most severely aggressive subtypes (i.e., borderline-dysphoric and generally violent-antisocial) were the most likely to report a history of head injury and to have significantly lower mean scores on a neuropsychological test of verbal intelligence. The possible role of neuropsychological factors in IPA perpetration and implications for prevention and intervention programs are discussed.     

Adaptive information design for outdoor augmented reality

Augmented Reality focuses on the enrichment of the user's natural field of view by consistent integration of text, symbols and interactive three-dimensional objects in real time. Placing virtual objects directly into the user's view in a natural context empowers highly dynamic applications. On the other hand, this necessitates deliberate choice of information design and density, in particular for deployment in hazardous environments like military combat scenarios. As the amount of information needed is not foreseeable and strongly depends on the individual mission, an appropriate system must offer adequate adaptation capabilities. The paper presents a prototypical, vehicle-mountable Augmented Reality vision system, designed for enhancing situation awareness in stressful urban warfare scenarios. Tracking, as one of the most crucial challenges for outdoor Augmented Reality, is accomplished by means of a Differential-GPS approach while the type of display to attach can be modified, ranging from ocular displays to standard LCD mini-screens. The overall concept also includes envisioning of own troops (blue forces), for which a multi-sensor tracking approach has been chosen. As a main feature, the system allows switching between different information categories, focusing on friendly, hostile, unidentified or neutral data. Results of an empirical study on the superiority of an in-view navigation cue approach conclude the paper.     

The Box–Cox Transformation and Non‐Iterative Estimation Methods for Ordinal Log‐Linear Models

Recently Beh and Farver investigated and evaluated three non‐iterative procedures for estimating the linear‐by‐linear parameter of an ordinal log‐linear model. The study demonstrated that these non‐iterative techniques provide estimates that are, for most types of contingency tables, statistically indistinguishable from estimates from Newton's unidimensional algorithm. Here we show how two of these techniques are related using the Box–Cox transformation. We also show that by using this transformation, accurate non‐iterative estimates are achievable even when a contingency table contains sampling zeros.     

Skin lighteners, Black consumers and Jewish entrepreneurs in South Africa

This article considers the rise and decline of South Africa's lucrative and controversial skin-lighteners market through examination of the business history of the largest manufacturers, Abraham and Solomon Krok, and their evolving personas as millionaires and philanthropists. Such examination reveals how the country's skin-lighteners trade emerged as part of the broader growth of a black consumer market after the Second World War and how elements of that market became the target of anti-apartheid protests in subsequent decades. It also demonstrates how the Kroks' experiences as second-generation Jewish immigrants shaped their involvement in the trade and how, later, their self-identification as Jewish philanthropists informed their efforts to rehabilitate their reputations following South Africa's 1990 ban on all skin lighteners. Such efforts include the building of Johannesburg's highly acclaimed Apartheid Museum, modelled after the United States Holocaust Memorial Museum. This article explores the profound ironies that some South Africans see in the fact that a museum dedicated to commemorating those who suffered under and, ultimately, triumphed against state racism was financed by a family fortune generated through the sale of skin lighteners to black consumers.     

Is the Precautionary Principle Really Incoherent?

The Precautionary Principle has been an increasingly important principle in international treaties since the 1980s. Through varying formulations, it states that when an activity can lead to a catastrophe for human health or the environment, measures should be taken to prevent it even if the cause‐and‐effect relationship is not fully established scientifically. The Precautionary Principle has been critically discussed from many sides. This article concentrates on a theoretical argument by Peterson (2006) according to which the Precautionary Principle is incoherent with other desiderata of rational decision making, and thus cannot be used as a decision rule that selects an action among several ones. I claim here that Peterson's argument fails to establish the incoherence of the Precautionary Principle, by attacking three of its premises. I argue (i) that Peterson's treatment of uncertainties lacks generality, (ii) that his Archimedian condition is problematic for incommensurability reasons, and (iii) that his explication of the Precautionary Principle is not adequate. This leads me to conjecture that the Precautionary Principle can be envisaged as a coherent decision rule, again.