On a class exhibiting trend change in average failure rate

Abstract

Weak convergence and moment convergence issues are investigated for the New Better than Average Failure Rate (NBAFR) family (introduced by Loh (1984 Loh, W. Y. 1984. A new generalization of the class of NBU distributions. IEEE Transactions on Reliability R-33 :97–113[Crossref], [Web of Science ®] , [Google Scholar])). We explore the validity of these results in the context of a more general ageing class that we introduce. We prove some new properties of this class and derive its interrelationships with other non-monotonic ageing families. Reliability and moment bounds are obtained and an interesting characterization of exponentiality is proved. Special cases of our results lead to new theorems for the NBAFR class. Finally weak convergence and related issues are established for this class.     

A fresh approach for intercession of nonresponse in multivariate longitudinal designs

The occurrence of nonresponse is very much plebeian in surveys, which troubles the analysis, and hence, an inappropriate inference is left out. To counterbalance the sour effects of the incompleteness, fresh imputation techniques have been proposed with the aid of multi-auxiliary variates for the estimation of population mean on successive waves. Properties of the proposed estimators have been elaborated, and they have been compared with the work of Priyanka et al. (2015). Detailed simulation study is carried out to substantiate the empirical and theoretical results. Several possible cases have been addressed in which nonresponse can occur.     

No city for migrant women: construction workers’ experiences of exclusion from urban governance and discrimination in labour markets in Ahmedabad

ABSTRACT

Ahmedabad, Gujarat, is one of the fastest growing cities in the world, and a reflection of India’s story of exclusionary economic growth. This article focuses on research carried out with women construction workers with the help of a migrant construction workers’ union in Ahmedabad. It describes the method used by women members of the union to make visible their experiences as migrants in the city – with men, local authorities, and employers – to highlight the additional burdens that they bear due to a negligent state and industry, advocate for better working and living conditions, and raise consciousness of gender inequalities that need to be integrated into the demands of the workers’ union.     

Estimation of Disaggregate-Level Poverty Incidence in Odisha Under Area-Level Hierarchical Bayes Small Area Model

Sustainable development goal-1 of the United Nations is to end poverty in all its forms everywhere. The estimates of poverty related parameters obtained from large scale sample survey are often available at large domain level (e.g. state level). But, poverty rates are not uniformly distributed across the regions. The regional variations are masked in such large domain level estimates. However, for monitoring the progress of poverty alleviation programmes aimed at reduction of poverty often require micro or disaggregate level estimates. The traditional survey estimation approaches are not suitable for generating the reliable estimates at this level because of sample size problem. It is the main endeavor of Small Area Estimation (SAE) approach to produce micro level statistics with acceptable precision without incurring any extra cost and utilizing existing survey data. In this study, the Hierarchical Bayes approach of SAE has been applied to generate reliable and representative district level poverty incidence for the State of Odisha in India using the Household Consumer Expenditure Survey 2011–2012 data of National Sample Survey Office and linked with Population Census 2011. The results show the precise performance of model based estimates generated by SAE method to a greater extent than the direct survey estimates. A poverty map has also been produced to observe the spatial inequality in poverty distribution.

     

Searching effective rotation patterns for population median using exponential type estimators in two-occasion rotation sampling

ABSTRACT

The present article is an attempt to explore the rotation patterns using exponential ratio type estimators for the estimation of finite population median at current occasion in two occasion rotation sampling. Properties of the proposed estimators including the optimum replacement strategies have been elaborated. The proposed estimators have been compared with sample median estimator when there is no matching from previous occasion as well with the ratio type estimator proposed by Singh et al. (2007 Singh, H.P., Tailor, R., Singh, S., Kim, Jong-Min. (2007). Quintile estimation in successive sampling. J. Kor. Stat. Soc. 36(4):543–556. [Google Scholar]) for second quantile. The behaviors of the proposed estimators are justified by empirical interpretations and validated by means of simulation study with the help of some natural populations.     

A composite class of estimators using scrambled response mechanism for sensitive population mean in successive sampling

This paper considers the problem of estimation of population mean of a sensitive characteristics using non-sensitive auxiliary variable at current move in two move successive sampling. The proposed estimator is studied under five different scrambled response models. Various estimators have been elaborated to be the member of the proposed class of estimators. The properties of the proposed estimators have been analysed. Many estimators belonging to the proposed class have been explored under five scrambled response models. In order to identify the scrambled model effect, the proposed composite class of estimators is compared to the direct methods. Respondents privacy protection have also been elaborated under different models. Theoretical results are supplemented with numerical demonstrations using real data. Simulation has been carried out to show the applicability of proposed estimators and hence suitable recommendations are forwarded.     

Bayes Predictor of One-Parameter Exponential Family Type Population Mean Under Balanced Loss Function

We obtain a Bayes predictor and a Bayes prediction risk of the mean of a finite population relative to the balanced loss function. The predictive expected losses associated with classical and standard Bayes predictors are derived and compared with that of a Bayes predictor under a balanced loss function. Specific expressions for a regular exponential family distributed superpopulation are presented and illustrated for some well-known superpopulations.     

Search of Good Rotation Patterns to Improve the Precision of Estimates at Current Occasion

In rotation (successive) sampling, it is common practice to use the information collected on a previous occasion to improve the precision of the estimates at current occasion. The previous information may be in the form of an auxiliary character, the character under study itself, or both. In the present work, information on an auxiliary character, which is readily available on all the occasions, has been used along with the information on study character from the previous and current occasion. Consequently, chain type difference and regression estimators have been proposed for estimating the population mean at second (current) occasion in the two occasions rotation (successive) sampling. The proposed estimators have been compared with sample mean estimator when there is no matching and the optimum estimator, which is the combination of the means of the matched and unmatched portions of the sample at the second occasion. Optimum replacement policy is also discussed. Theoretical results have been justified through empirical interpretation.     

Factors affecting mosquito populations in created wetlands in urban landscapes

Constructed, created and restored wetlands are gaining popularity in urban areas due to many ecosystem services they provide. However, there is a concern over mosquito breeding in such wetlands. We studied factors affecting mosquito populations in two experimental flow-through created wetlands, a stormwater wetland, a pond and 40 mono-specific and mixed plant mesocosms (1?m²) at the Olentangy River Wetland Research Park (ORWRP) in Columbus, Ohio. The flow-through created wetlands had less mosquito larval density (2 to 4/dip) compared to the pond (36.2?±?8.4/dip) (p?<?0.00001) and stormwater wetland (24.9?±?10.2/dip) (p?=?0.002). Sites with higher larval density in the flow-through wetlands were outflow regions (p?=?0.009) and emergent vegetation sites (p?=?0.023). Mixed vegetation communities consisting of Sparganium eurycarpum, Juncus effusus, and Schoenoplectus tabernaemontani rather than mono specific Typha communities provided most conducive environment for mosquito breeding (p?<?0.0001). Mesocosm plots with steady inflow (10?cm depth) and deep water (20?cm) in summer and shallow water (5?cm) in spring had higher mosquito densities than mesocosm plots with other hydrological conditions. Among water quality parameters, conductivity (p?=?0.004) positively and dissolved oxygen (p?=?0.052) negatively correlated with mosquito larval density. Six mosquito species identified in all water bodies were Culex pipiens, Culex salinarius, Culex restuans, Uranotaenia sapphirina, Anopheles quadrimaculatus, and Anopheles punctipennis some of which may transmit deadly human pathogens. This information will be useful for targeting mosquito populations in specific sections of urban created wetlands and to develop improved designs for urban wetlands.     

Model-based study of families of exponential-type estimators in presence of non response

Among other types of non sampling errors, non response error (NRE) is an inherent component of any sample survey, which is supposed to be given much attention during the designing and execution stages. With increasing awareness of these estimators, therefore, there is an urge for the development of suitable techniques for controlling them.

This article proposes two families of estimators for population mean in the presence of non response and discuses various properties under model approach, namely polynomial regression model. The families include some existing estimators. Comparison of efficiencies along with the robustness of the estimators under misspecification of models has been empirically discussed.