Private equity regulation: a comparative analysis

This article examines the existing contractual arrangements and industry standards in private equity. It shows that investors are, in principle, capable of structuring their particular investments according to their own preferences, there are a range of governance problems and risks that could be potentially hazardous for some classes of investors. We examine the circumstances where existing industry codes and legal tools can be used to address the problems that arise in relation to private equity and buyout activity.     

Romantic relationships,college student alcohol use,and negative consequences of drinking

This study examined whether being in a romantic relationship is associated with undergraduates’ alcohol use and negative consequences of drinking. Alcohol use was operationalized to include amount and frequency of drinking, binge drinking, and drunkenness. Negative consequences included: having a hangover, missing a class, getting behind in school work, doing something that was later regretted, forgetting where the student was or what they did, having unplanned sex, and getting hurt or injured. Data came from an online survey distributed to Midwestern undergraduate students (N = 572), with analyses conducted separately for men and women. Results indicated that being in a committed relationship generally served as a protective factor against drunkenness, but did not reduce frequency of drinking or binge drinking. Whereas romantically committed men were only less likely to report doing something that was later regretted, women in romantic relationships were less likely to experience all negative consequences of drinking considered here.     

Modeling probability density through ultraspherical polynomial transformations

We present a method for fitting parametric probability density models using an integrated square error criterion on a continuum of weighted Lebesgue spaces formed by ultraspherical polynomials. This approach is inherently suitable for creating mixture model representations of complex distributions and allows fully autonomous cluster analysis of high-dimensional datasets. The method is also suitable for extremely large sets, allowing post facto model selection and analysis even in the absence of the original data. Furthermore, the fitting procedure only requires the parametric model to be pointwise evaluable, making it trivial to fit user-defined models through a generic algorithm.     

Impact of an Overt Response System on Staff Performance and Maintenance of Computer-Based Instruction

Interactive Computer Based Instruction (CBI) systems involve teaching strategies to facilitate greater response opportunities during training in an effort to improve learner performance. The current study investigated the effect of online staff training videos with and without overt response requirements on posttest and maintenance test scores across six block-randomized instructional modules for four employees of a university located in the southeastern region of the United States. The overt response consisted of multiple-choice questions administered throughout select teaching modules using an alternating treatment design. Findings suggest that learning occurred as a result of the CBI training; however, the effectiveness of the overt response system varied across individuals, with no discernible differentiation between learning gains associated with response requirements. Other areas of research for expanding the efficacy of CBI and overt response systems are highlighted.     

Optimal design of repetitive group sampling plans for Weibull and gamma distributions with applications and comparison to the Birnbaum–Saunders distribution

In this paper, we propose a multiple deferred state repetitive group sampling plan which is a new sampling plan developed by incorporating the features of both multiple deferred state sampling plan and repetitive group sampling plan, for assuring Weibull or gamma distributed mean life of the products. The quality of the product is represented by the ratio of true mean life and specified mean life of the products. Two points on the operating characteristic curve approach is used to determine the optimal parameters of the proposed plan. The plan parameters are determined by formulating an optimization problem for various combinations of producer's risk and consumer's risk for both distributions. The sensitivity analysis of the proposed plan is discussed. The implementation of the proposed plan is explained using real-life data and simulated data. The proposed plan under Weibull distribution is compared with the existing sampling plans. The average sample number (ASN) of the proposed plan and failure probability of the product are obtained under Weibull, gamma and Birnbaum–Saunders distributions for a specified value of shape parameter and compared with each other. In addition, a comparative study is made between the ASN of the proposed plan under Weibull and gamma distributions.     

Conditional covariance penalties for mixed models

The prediction error for mixed models can have a conditional or a marginal perspective depending on the research focus. We introduce a novel conditional version of the optimism theorem for mixed models linking the conditional prediction error to covariance penalties for mixed models. Different possibilities for estimating these conditional covariance penalties are introduced. These are bootstrap methods, cross-validation, and a direct approach called Steinian. The behavior of the different estimation techniques is assessed in a simulation study for the binomial-, the t-, and the gamma distribution and for different kinds of prediction error. Furthermore, the impact of the estimation techniques on the prediction error is discussed based on an application to undernutrition in Zambia.     

Coordinate sampler: a non-reversible Gibbs-like MCMC sampler

We derive a novel non-reversible, continuous-time Markov chain Monte Carlo sampler, called Coordinate Sampler, based on a piecewise deterministic Markov process, which is a variant of the Zigzag sampler of Bierkens et al. (Ann Stat 47(3):1288–1320, 2019). In addition to providing a theoretical validation for this new simulation algorithm, we show that the Markov chain it induces exhibits geometrical ergodicity convergence, for distributions whose tails decay at least as fast as an exponential distribution and at most as fast as a Gaussian distribution. Several numerical examples highlight that our coordinate sampler is more efficient than the Zigzag sampler, in terms of effective sample size.     

Activity patterns and temporal niche partitioning of dogs and medium-sized wild mammals in urban parks of Xalapa,Mexico

Urban Ecosystems - Free-ranging domestic dogs are the world most common exotic carnivore species that could negatively interact with the native wildlife as predators, competitors, and disease...     

The Aversion to Tampering with Nature (ATN) Scale: Individual Differences in (Dis)comfort with Altering the Natural World

People differ in their comfort with tampering with the natural world. Although some see altering nature as a sign of human progress, others see it as dangerous or hubristic. Across four studies, we investigate discomfort with tampering with the natural world. To do so, we develop the Aversion to Tampering with Nature (ATN) Scale, a short scale that is the first to directly measure this discomfort. We identify six activities that people believe tamper with nature (geoengineering, genetically modified organisms, pesticides, cloning, gene therapy, and nanoparticles) and show that ATN scores are associated with opposition to these activities. Furthermore, the ATN Scale predicts actual behavior: donations to an anti-tampering cause. We demonstrate that ATN is related to previously identified constructs including trust in technology, naturalness bias, purity values, disgust sensitivity, aversion to playing God, and environmental beliefs and values. By illuminating who is concerned about tampering with nature and what predicts these beliefs, the ATN Scale provides opportunities to better understand public opposition to technological innovations, consumer preferences for “natural” products, and strategies for science communication.