On Optimality of Bayesian Wavelet Estimators

Abstract.  We investigate the asymptotic optimality of several Bayesian wavelet estimators, namely, posterior mean, posterior median and Bayes Factor, where the prior imposed on wavelet coefficients is a mixture of a mass function at zero and a Gaussian density. We show that in terms of the mean squared error, for the properly chosen hyperparameters of the prior, all the three resulting Bayesian wavelet estimators achieve optimal minimax rates within any prescribed Besov space     for p  ≥ 2. For 1 ≤  p  < 2, the Bayes Factor is still optimal for (2 s +2)/(2 s +1) ≤  p  < 2 and always outperforms the posterior mean and the posterior median that can achieve only the best possible rates for linear estimators in this case.     

Is the Association Between Education and Fertility Postponement Causal? The Role of Family Background Factors

A large body of literature has demonstrated a positive relationship between education and age at first birth. However, this relationship may be partly spurious because of family background factors that cannot be controlled for in most research designs. We investigate the extent to which education is causally related to later age at first birth in a large sample of female twins from the United Kingdom (N = 2,752). We present novel estimates using within–identical twin and biometric models. Our findings show that one year of additional schooling is associated with about one-half year later age at first birth in ordinary least squares (OLS) models. This estimate reduced to only a 1.5-month later age at first birth for the within–identical twin model controlling for all shared family background factors (genetic and family environmental). Biometric analyses reveal that it is mainly influences of the family environment—not genetic factors—that cause spurious associations between education and age at first birth. Last, using data from the Office for National Statistics, we demonstrate that only 1.9 months of the 2.74 years of fertility postponement for birth cohorts 1944–1967 could be attributed to educational expansion based on these estimates. We conclude that the rise in educational attainment alone cannot explain differences in fertility timing between cohorts.     

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.     

Socioeconomic System of the Oil Boom and Rural Community Development in Western North Dakota

An oil boom is a complex social and economic phenomenon. The socioeconomic system presented in this article represents a novel effort to explicate boom impacts and changes, within a systems framework, at the community level to enhance community planning and development efforts. Most boomtown studies focus on longitudinal changes of a boom‐bust‐recovery cycle or social‐disruption‐based approaches. This article is an effort to demonstrate that longitudinal changes or social disruptions of a boom manifest through the interactions and interrelationships between social entities and stakeholders acting within the boom conditions and surrounding conditions. The socioeconomic system approach in this article analyzes the boom as a system, which provides a useful lens for many other rural communities currently experiencing unconventional oil and gas development in the United States. The socioeconomic system highlights five main challenges or factors that need to be addressed through community development strategies: develop affordable housing, invest in community infrastructure, expand public services, attract new businesses to the area, and develop better community integration strategies to build trust and unity within the community. This article is qualitative and exploratory in nature. As a result, it explicates the functions, structure, and relationships between system entities to provide a broader understanding of coherence, conflicts, and synergies within a system.     

Additive mixed models with approximate Dirichlet process mixtures: the EM approach

We consider additive mixed models for longitudinal data with a nonlinear time trend. As random effects distribution an approximate Dirichlet process mixture is proposed that is based on the truncated version of the stick breaking presentation of the Dirichlet process and provides a Gaussian mixture with a data driven choice of the number of mixture components. The main advantage of the specification is its ability to identify clusters of subjects with a similar random effects structure. For the estimation of the trend curve the mixed model representation of penalized splines is used. An Expectation-Maximization algorithm is given that solves the estimation problem and that exhibits advantages over Markov chain Monte Carlo approaches, which are typically used when modeling with Dirichlet processes. The method is evaluated in a simulation study and applied to theophylline data and to body mass index profiles of children.     

‘I Want to Persuade You!’ – Investigating the effectiveness of explicit persuasion concerning attributes of the communicator and the marketing campaign

In explicit persuasion, the communicator states explicitly a desire to persuade the consumer. By referring to an attributional approach, social engagement was simultaneously explored as a beneficial communicator attribute, while cause-related marketing (CRM) was addressed as a boundary condition. In an experiment, we varied the persuasion strategy (explicit vs. implicit), the communicator’s prior experience with social engagement (yes vs. no), and the specific marketing strategy (CRM vs. non-charity marketing). As expected, in the non-charity marketing condition, explicit (vs. implicit) persuasion was more effective when the communicator had prior experience in social engagement. In the CRM condition, explicit (vs. implicit) persuasion was less effective when the communicator had prior experience in social engagement; when no prior experience was reported, persuasiveness increased.     

Consistent Probabilistic Social Choice

Two fundamental axioms in social choice theory are consistency with respect to a variable electorate and consistency with respect to components of similar alternatives. In the context of traditional non‐probabilistic social choice, these axioms are incompatible with each other. We show that in the context of probabilistic social choice, these axioms uniquely characterize a function proposed by Fishburn (1984). Fishburn's function returns so‐called maximal lotteries, that is, lotteries that correspond to optimal mixed strategies in the symmetric zero‐sum game induced by the pairwise majority margins. Maximal lotteries are guaranteed to exist due to von Neumann's Minimax Theorem, are almost always unique, and can be efficiently computed using linear programming.     

Open Innovation in Nonprofit Sports Clubs

This research paper investigates open innovation—that is, the use of purposive inflows and outflows of knowledge in order to innovate—in the context of nonprofit sports clubs, and is based on the content analysis of semi-structured interviews held with representatives of eleven sports clubs. The study develops a framework that describes open innovation activities in nonprofit sports clubs as facets of four superordinate dimensions, namely permeability of the club’s boundary, application and implementation of open innovation practices, managerial competencies, and the environmental and organizational surroundings in which the club operates. Within these dimensions, subordinate facets such as commitment of the club’s president and the strategic use of coopetitive environments explain how and why sports clubs are successful at implementing innovations and how their nonprofit status (e.g., volunteer work) contributes to (or is in conflict with) innovation. The findings provide implications for nonprofit organizations inside and outside the sports sector.     

Einkommenseffekte beruflicher Weiterbildung

The claim for lifelong learning or vocational further training is most often set out without having clarified satisfactorily the individual gains which result from training activities. Based on human capital theory, which we extend by arguments from signaling- and game theory, the paper investigates for western and eastern Germany individual returns of training on income with longitudinal data (1996–1998) from the recently available “Mikrozensus-Panel”. A problem in identifying causal training effects is a selection bias caused by unobserved heterogeneity which – using conventional methods – leads to overestimation of the effects. Fixed- and Random-Effects-Models – which we discuss and confront empirically regarding the training issue – present a method for controlling the selection bias. The results show evidence for positive and significant training effects on income, although the actual amount of income growth is low. Whereas no differences by sex were found, separate analyses by age, skill levels and region indicate that not all of the subgroups benefit positively from further training activities. Therefore, the findings relativize the importance of social inequalities in the access to further training for the process of status attainment in general.