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.     

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.     

The exponential distribution analog of the Grubbs–Weaver method

Abstract

Grubbs and Weaver (1947 Grubbs, F. E., and C. L. Weaver. 1947. The best unbiased estimate of population standard deviation based on group ranges. Journal of the American Statistical Association 42 (238):224–41. doi: 10.2307/2280652.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) suggest a minimum-variance unbiased estimator for the population standard deviation of a normal random variable, where a random sample is drawn and a weighted sum of the ranges of subsamples is calculated. The optimal choice involves using as many subsamples of size eight as possible. They verified their results numerically for samples of size up to 100, and conjectured that their “rule of eights” is valid for all sample sizes. Here we examine the analogous problem where the underlying distribution is exponential and find that a “rule of fours” yields optimality and prove the result rigorously.     

20 years of Bologna - a story of success,a story of failure

The Bologna Process is a unique harmonisation process taking place outside the policy-making framework of the European Union. It aims at enhancing the comparability and compatibility of higher education structures and degrees across Europe, as well as to institutionalise quality assurance mechanisms. The aim of this article is to provide a condensed, up-to-date overview of the Bologna Process with regard to structural characteristics, before embedding it into a discussion on processes on voluntary policy convergence and to which extent we should be able to find this kind of policy harmonisation in the realm of the Bologna Process. Related to this are questions why this, in principle, completely voluntary process of policy harmonisation, has appealed to so many countries and why they might or might not feel committed to the implementation of its policies and tools.     

USING THE PARETO DISTRIBUTION TO IMPROVE ESTIMATES OF TOPCODED EARNINGS

Inconsistent censoring in the public‐use March Current Population Survey (CPS) limits its usefulness in measuring labor earnings trends, as previous approaches for imputing topcoded earnings systematically understate top earnings. Using Pareto estimation methods with less‐censored internal data, we create an enhanced cell‐mean series to capture top earnings in the public‐use data. Annual earnings inequality trends since 1963 using our series largely mirror those found by Kopczuk, Saez, and Song using social security administration data for commerce and industry workers. When we extend our analysis to 2013 and consider all workers, earnings inequality levels are higher but its growth is more modest. (JEL C81, D31, J01)     

Predictive Hierarchic Modeling of Operational Characteristics in Clinical Trials

An analytic methodology for patient enrollment modeling using a Poisson-gamma model is developed by Anisimov & Fedorov (2005–2007). For modeling hierarchic processes associated with enrollment, a new methodology using evolving stochastic processes is proposed. This provides rather general and unified framework to describe various operational processes associated with enrollment. The technique for calculating predictive distributions, mean, and credibility bounds for evolving processes is developed. Some applications to modeling operational characteristics in clinical trials are considered with focus to modeling events associated with incoming and follow-up patients in different settings. For these models, predictive characteristics are derived in a closed form.