Mean Time to Failure of Weighted k-out-of-n: G Systems

The purpose of this article is to develop a Monte-Carlo simulation algorithm for computing mean time to failure (MTTF) of weighted-k-out-of-n:G and linear consecutive-weighted-k-out-of-n:G systems. Our algorithm is based on the use of appropriately defined stochastic process which represents the total weight of the system at time t. These stochastic processes are explicitly defined and used along with the ordered component lifetimes to simulate MTTF of the systems with weighted components.     

近十五年西方历史学的新发展

20世纪后期,历史研究的重点继续是从分析的社会科学转移到更加强调文化因素的方面来,但是面临着迅速变化的世界局面,却具有其更加繁富且已改变了的焦点。历史学家并未受到后现代主义太多的影响,但关于应该如何重铸过去的问题的确更趋复杂了。在历史学思想与实践的重新定向过程中,人们更为深入地反思和质疑了历史作为引向今日西方文明的一种单向历程的观念,政治领域和阶级的概念扩大或改变了,妇女与性别的历史日益被纳入到通史系统中来。而在迫切需要另行考察现代性以及撰写全球史的状况面前,我们对于广泛跨文化的方法仍然缺乏综合的认知,有待于未来的进一步规划。     

A model of the Canadian global exchange rate: A test of the 1970s

This comment points out some methodological weaknesses in the Canadian global exchange rate model and the associated efficiency tests of Marwah and Bodkin. The model is found to be inadequate for policy analysis.     

Robust gene–environment interaction analysis using penalized trimmed regression

ABSTRACT

In biomedical and epidemiological studies, gene–environment (G–E) interactions have been shown to importantly contribute to the etiology and progression of many complex diseases. Most existing approaches for identifying G–E interactions are limited by the lack of robustness against outliers/contaminations in response and predictor spaces. In this study, we develop a novel robust G–E identification approach using the trimmed regression technique under joint modelling. A robust data-driven criterion and stability selection are adopted to determine the trimmed subset which is free from both vertical outliers and leverage points. An effective penalization approach is developed to identify important G–E interactions, respecting the ‘main effects, interactions’ hierarchical structure. Extensive simulations demonstrate the better performance of the proposed approach compared to multiple alternatives. Interesting findings with superior prediction accuracy and stability are observed in the analysis of The Cancer Genome Atlas data on cutaneous melanoma and breast invasive carcinoma.     

Approximating M/G/1 Waiting Time Tail Probabilities

Abstract

We propose a new approximation formula for the waiting time tail probability of the M/G/1 queue with FIFO discipline and unlimited waiting space. The aim is to address the difficulty of obtaining good estimates when the tail probability has non-exponential asymptotics. We show that the waiting time tail probability can be expressed in terms of the waiting time tail probability of a notional M/G/1 queue with truncated service time distribution plus the tail probability of an extreme order statistic. The Cramér–Lundberg approximation is applied to approximate the tail probability of the notional queue. In essence, our technique extends the applicability of the Cramér–Lundberg approximation to cases where the standard Lundberg condition does not hold. We propose a simple moment-based technique for estimating the parameters of the approximation; numerical results demonstrate that our approximation can yield very good estimates over the whole range of the argument.     

屠隆与普陀十二景

普陀山雄奇幽灵的自然景观，经历代文人题咏，便有了人文品格，成为山水风景社会化的显著标志。明代戏剧家屠隆首题普陀山十二景，并且是《普陀十二景诗》的始作俑者，对后世有较大影响。