A Bayes comparison of Weibull extension and modified Weibull models for data showing bathtub hazard rate

A number of models have been proposed in the literature to model data reflecting bathtub-shaped hazard rate functions. Mixture distributions provide the obvious choice for modelling such data sets but these contain too many parameters and hamper the accuracy of the inferential procedures particularly when the data are meagre. Recently, a few distributions have been proposed which are simply generalizations of the two-parameter Weibull model and are capable of producing bathtub behaviour of the hazard rate function. The Weibull extension and the modified Weibull models are two such families. This study focuses on comparing these two distributions for data sets exhibiting bathtub shape of the hazard rate. Bayesian tools are preferred due to their wide range of applicability in various nested and non-nested model comparison problems. Real data illustrations are provided so that a particular model can be recommended based on various tools of model comparison discussed in the paper.     

A Data‐Driven Approach to Assessing Supply Inadequacy Risks Due to Climate‐Induced Shifts in Electricity Demand

The U.S. electric power system is increasingly vulnerable to the adverse impacts of extreme climate events. Supply inadequacy risk can result from climate‐induced shifts in electricity demand and/or damaged physical assets due to hydro‐meteorological hazards and climate change. In this article, we focus on the risks associated with the unanticipated climate‐induced demand shifts and propose a data‐driven approach to identify risk factors that render the electricity sector vulnerable in the face of future climate variability and change. More specifically, we have leveraged advanced supervised learning theory to identify the key predictors of climate‐sensitive demand in the residential, commercial, and industrial sectors. Our analysis indicates that variations in mean dew point temperature is the common major risk factor across all the three sectors. We have also conducted a statistical sensitivity analysis to assess the variability in the projected demand as a function of the key climate risk factor. We then propose the use of scenario‐based heat maps as a tool to communicate the inadequacy risks to stakeholders and decisionmakers. While we use the state of Ohio as a case study, our proposed approach is equally applicable to all other states.     

Simultaneous semi-sequential testing of dual alternatives for pattern recognition

In this paper, we propose a new nonparametric simultaneous test for dual alternatives. Simultaneous tests for dual alternatives are used for pattern detection of arsenic contamination level in ground water. We consider two possible patterns, namely, monotone shift and an umbrella-type location alternative, as the dual alternatives. Pattern recognition problems of this nature are addressed in Bandyopadhyay et al. [5], stretching the idea of multiple hypotheses tests as in Benjamini and Hochberg [6]. In the present context, we develop an alternative approach based on contrasts that helps us to detect three underlying pattern much more efficiently. We illustrate the new methodology through a motivating example related to highly sensitive issue of arsenic contamination in ground water. We provide some Monte-Carlo studies related to the proposed technique and give a comparative study between different detection procedures. We also obtain some related asymptotic results.     

Methodological Validation of Quality of Life Questionnaire for Coal Mining Groups-Indian Scenario

Maslow’s hierarchy-of-needs theory has been used to predict development of Quality of Life (QOL) in countries over time. In this paper an attempt has been taken to derive a methodological validation of quality of life questionnaire which have been prepared for the study area. The objective of the study is to standardize a questionnaire tool to assess the QoL of residents in a problem area in India. From a pre tested 16 parameter questionnaire tool factorial validity were established to extract three domains and were mapped in accordance to Abraham Maslow’s Hierarchy of Needs theory. Out of these 16 parameters 13 were found relevant. Then a new tool was conceptualized with 13 pre selected parameters and other parameters were pooled from existing tool and reviews to form a 36 parameter tool. Factor analysis was done to extract the domains. Reliability of the tool was also tested to find the relation between the domains of QoL. Then the quality of life of the study area was interpreted to find the distribution of respondents among the categories of QoL. 70% of respondents reported to have average quality of life. The tool was found to be highly reliable and valid.     

An Exploratory Study of Older Adults' Engagement with Virtual Volunteerism

Virtual volunteering refers to the use of the Internet for volunteer services. It is an emerging phenomenon among every age group; however, the current study examines if it is a viable option for older people. Older adults are the fastest growing Internet users. They are also more civic minded than younger generations, thus the purpose of this study is to explore this relatively new area research. Data for this study have been collected using qualitative tools such as semistructured, partly open-ended interviews with older virtual volunteers affiliated with SeniorNet, an organization that facilitates virtual volunteering exclusively for older people. The study ends with suggestions for future research directions. Implications of this study include reconceptualization of virtual volunteering as a strategic tool to recruit older adults and greater usage of information communication technologies to promote civic engagement among older people and, thus, positively influence their health and well-being.     

Ranking Income Distributions by Deprivation Orderings

This paper has examined the problem of ranking income distributions using absolute deprivation ordering. It appears that the ranking of distributions by this ordering may be more unambiguous than that generated by the relative deprivation ordering. The class of average deprivation indices consistent with the absolute deprivation criterion is also identified.     

Bayesian and likelihood-based inference for the bivariate normal correlation coefficient

The paper develops some objective priors for correlation coefficient of the bivariate normal distribution. The criterion used is the asymptotic matching of coverage probabilities of Bayesian credible intervals with the corresponding frequentist coverage probabilities. The paper uses various matching criteria, namely, quantile matching, highest posterior density matching, and matching via inversion of test statistics. Each matching criterion leads to a different prior for the parameter of interest. We evaluate their performance by comparing credible intervals through simulation studies. In addition, inference through several likelihood-based methods have been discussed.     

Accelerated test system strength models based on Birnbaum–Saunders distribution: a complete Bayesian analysis and comparison

Several models for studies related to tensile strength of materials are proposed in the literature where the size or length component has been taken to be an important factor for studying the specimens’ failure behaviour. An important model, developed on the basis of cumulative damage approach, is the three-parameter extension of the Birnbaum–Saunders fatigue model that incorporates size of the specimen as an additional variable. This model is a strong competitor of the commonly used Weibull model and stands better than the traditional models, which do not incorporate the size effect. The paper considers two such cumulative damage models, checks their compatibility with a real dataset, compares them with some of the recent toolkits, and finally recommends a model, which appears an appropriate one. Throughout the study is Bayesian based on Markov chain Monte Carlo simulation.     

Structure and processes of a phenomenon: The context of quality of life in India

The properties of objective or subjective variables are commonly examined with reference to a set of mutually distinct but analogous social groups structured at a time point. The procedure fails to examine what is happening across the structured groups and therefore what is likely to be the role of the variables in differentiating or integrating the ordained set of social groups. A resolution of this issue is vital for the appraisal of a better quality of life because by definition it is always an ongoing phenomenon. The issue is examined with reference to its methodological implications and with respect to QOL data on India.