Measurement of socio-economic inequality using the Life-Quality Index

As income inequality presents a narrow view of overall inequality prevailing in a society, the paper focuses on its much broader definition, referred to as socio-economic inequality, which considers the disparities in income as well as in mortality, and standard of living. The paper presents a new method for measuring the socio-economic inequality using a composite social indicator, Life-Quality Index, derived from two principal indicators of development, namely, the Real Gross Domestic Product per person and the life expectancy at birth. Income inequality and the associated life expectancy variations are integrated into a quality adjusted income (QAI), to account for the observed differentials in life-quality of various quintiles of the population. The Gini coefficient of the distribution of QAI is introduced as a measure of socio-econmic inequality. The proposed approach is illustrated using data on life expectancy of five income quintiles in urban Canada. It is found that the magnitude of inequality in Canada is higher than that reflected by the traditional measure, the Gini coefficient of income.     

Victimization in young urban adults and depressed mood: understanding the interplay of coping and gender

Violence exposure has a significant impact on victims' psychological well-being. This study examined the relationship between two types of violence exposures (threats and physical assaults), coping styles (emotion focused, avoidant, and problem focused), gender, and depression among 211 (147 females and 64 males) young urban adults (ages 18-24). Most participants (60%) endorsed being physically assaulted, whereas many (40%) endorsed being threatened. Hierarchical multiple regressions were conducted. As hypothesized, women reported using more emotion-focused coping and reported greater depression than men. Avoidant coping was a predictor for increased depression for both men and women. However, women who employed problem-focused coping after their first physical assault reported lower rates of depression. These findings have implications for designing early interventions.     

Shared frailty models with baseline generalized Pareto distribution

Abstract

In this article, we have considered three different shared frailty models under the assumption of generalized Pareto Distribution as baseline distribution. Frailty models have been used in the survival analysis to account for the unobserved heterogeneity in an individual risks to disease and death. These three frailty models are with gamma frailty, inverse Gaussian frailty and positive stable frailty. Then we introduce the Bayesian estimation procedure using Markov chain Monte Carlo (MCMC) technique to estimate the parameters. We applied these three models to a kidney infection data and find the best fitted model for kidney infection data. We present a simulation study to compare true value of the parameters with the estimated values. Model comparison is made using Bayesian model selection criterion and a well-fitted model is suggested for the kidney infection data.     

Shrinkage testimators for the shape parameter of weibull distributin under type ii censoring

In this paper we propose some shrinkage testimators for the shape parameter of the Weibull distribution when censored samples are available and study their properties. Comparison of the testimators with Singh and Bhatkulikar (1978) and with the usual estimator, interms of mean squared error are made. It is shown that the proposed testimators     

Algorithmic aspects of <Emphasis Type="Italic">b</Emphasis>-disjunctive domination in graphs

For a fixed integer \(b>1\), a set \(D\subseteq V\) is called a b-disjunctive dominating set of the graph \(G=(V,E)\) if for every vertex \(v\in V{\setminus }D\), v is either adjacent to a vertex of D or has at least b vertices in D at distance 2 from it. The Minimum b-Disjunctive Domination Problem (MbDDP) is to find a b-disjunctive dominating set of minimum cardinality. The cardinality of a minimum b-disjunctive dominating set of G is called the b-disjunctive domination number of G, and is denoted by \(\gamma _{b}^{d}(G)\). Given a positive integer k and a graph G, the b-Disjunctive Domination Decision Problem (bDDDP) is to decide whether G has a b-disjunctive dominating set of cardinality at most k. In this paper, we first show that for a proper interval graph G, \(\gamma _{b}^{d}(G)\) is equal to \(\gamma (G)\), the domination number of G for \(b \ge 3\) and observe that \(\gamma _{b}^{d}(G)\) need not be equal to \(\gamma (G)\) for \(b=2\). We then propose a polynomial time algorithm to compute a minimum cardinality b-disjunctive dominating set of a proper interval graph for \(b=2\). Next we tighten the NP-completeness of bDDDP by showing that it remains NP-complete even in chordal graphs. We also propose a \((\ln ({\varDelta }^{2}+(b-1){\varDelta }+b)+1)\)-approximation algorithm for MbDDP, where \({\varDelta }\) is the maximum degree of input graph \(G=(V,E)\) and prove that MbDDP cannot be approximated within \((1-\epsilon ) \ln (|V|)\) for any \(\epsilon >0\) unless NP \(\subseteq \) DTIME\((|V|^{O(\log \log |V|)})\). Finally, we show that MbDDP is APX-complete for bipartite graphs with maximum degree \(\max \{b,4\}\).     

Construction of the Scale-Specific Resilience Index to Facilitate Multiscale Decision Making in Disaster Management: A Case Study of the 2015 Nepal Earthquake

Social Indicators Research - Many scholars have advocated for the use of empirical evidence to assess resilience across scales and over time. Accordingly, we conduct a case study using survey data...     

Bayesian estimation of mean and square of mean of normal distribution using linex loss function

In this paper, the Bayes estimators for mean and square of mean ol a normal distribution with mean μ and vaiiance σ r2 (known), relative to LINEX loss function are obtained Comparisons in terms of risk functions and Bayes risks of those under LINEX loss and squared error loss functions with their respective alternative estimators viz, UMVUE and Bayes estimators relative to squared error loss function, are made. It is found that Bayes estimators relative to LINEX loss function dominate the alternative estimators m terms of risk function snd Bayes risk. It is also found that if t2 is unknown the Bayes estimators are still preferable over alternative estimators.