L-moments of residual life

The mean, variance and coefficient of variation of residual life which are based on the usual moments of the residual life distribution are extensively used in reliability analysis. It has been established in various theoretical and empirical studies that the L-moments have some advantages over the usual moments in many situations. Accordingly in the present paper we study the properties of L-moments of residual life in the context of modeling lifetime data, characterizing life distributions and other applications. The role of certain quantile functions and quantile-based concepts in reliability analysis are also investigated.     

A Method for Evaluating Transmission Line Magnetic Field Mitigation Strategies That Incorporates Biological Uncertainty

A method to determine how much reduction in public exposure to power frequency magnetic fields can be obtained for different levels of investment is presented. Which if any "effects function" best describes the relationship between field exposure and biological effect is uncertain at this time. Also, in a particular context such as construction of new transmission lines there are a variety of different technologies which might be used to reduce exposure. We describe and demonstrate a method by which exposure reduction supply curves (i.e., the cost of purchasing different amounts of exposure reduction given various mitigation options) can be estimated parametrically for different exposure conditions and effects functions, and we display illustrative results.     

The New Zenga curve in the context of reliability analysis

ABSTRACT

In this article, we look into the properties and characterizations of the New Zenga curve. The relationship of the curve with other measures of inequality as well as some reliability concepts are examined. Classification of lifetime distributions using the Zenga curve and an illustration for the behaviour of the curve using a survival data are also provided.     

Quantile-based cumulative Kullback–Leibler divergence

The paper introduces a quantile-based cumulative Kullback–Leibler divergence and study its various properties. Unlike the distribution function approach, the quantile-based measure possesses some unique properties. The quantile functions used in many applied works do not have any tractable distribution functions where the proposed measure is a useful tool to compute the distance between two random variables. Some useful bounds are obtained for quantile-based residual cumulative Kullback–Leibler divergence and quantile-based reliability measures. Characterization results based on the functional forms of quantile-based residual Kullback–Leibler divergence are obtained for some well-known life distributions, namely exponential, Pareto II and beta.     

The Negative Effects of Social Capital in Organizations: A Review and Extension

Numerous studies have examined the positive effects of social capital in organizations, whereas the possible negative effects have attracted considerably less scholarly attention. To rectify this imbalance, this paper first undertakes a rigorous review of the published scholarly empirical evidence pertaining to the negative effects of social capital in organizations through a search of Web of Knowledge and Scopus, and then enumerates six potentially negative effects arising from increased levels of social capital. The review focuses on negative effects arising from bonding social capital and those arising from dense networks and closure, advancing new theory to elucidate the generative mechanisms that give rise to the proposed negative effects. Finally, the authors identify potential moderators of the negative effects thus theorized. Using the lens of social identification theory, the authors argue that dysfunctional identification processes restrict the processing of information and stimulate over‐commitment to established relationships, diluting in turn the dialectical process, and inhibiting individual learning within organizations, culminating in groupthink, the postponement of structural adjustments, the non‐rational escalation of commitment, and the blurring of firms’ boundaries. This review thus furthers the agenda of a more balanced inquiry into the effects of social capital in organizations.     

On dynamic weighted survival entropy of order α

Recently, Abbasnejad et al. (2010 Abbasnejad, M., Arghami, N.R., Morgenthaler, S., Mohtashami Borzadaran, G.R. (2010). On the dynamic survival entropy. Stat. Probab. Lett. 80:1962–1971.[Crossref], [Web of Science ®] , [Google Scholar]) proposed a measure of uncertainty based on survival function, called the survival entropy of order α. A dynamic form of the survival entropy of order α is also proposed by them. In this paper, we derive the weighted form of these measures. The properties of the new measures are also discussed.     

Chernoff distance for truncated distributions

In the present paper we extend the definition of Chernoff distance considered in Akahira (Ann Inst Stat Math 48:349–364, 1996) for truncated distributions and examine its properties. The relationship of this measure with other discrimination measures is examined. We study Chernoff distance between the original and weighted distributions. We also provide a characterization result for the proportional hazards model using the functional form of Chernoff distance.     

A new measure of association for bivariate survival data

Time dependent association measures between variables are of interest in bivariate survival data. Several such measures have been proposed in literature for the modelling and analysis of survival data. In this paper, we introduce a new measure of association for bivariate survival data using product moment residual life function and mean residual life function. Various properties of the proposed measure and its relationship with existing measures are discussed. We also develop a non-parametric estimator of the measure and study its asymptotic properties. The application of the result is illustrated using a real life data. Finally, a stimulation study is carried out to assess the performance of the estimator.