Estimating the distribution function using k-tuple ranked set samples

The basic assumption underlying the concept of ranked set sampling is that actual measurement of units is expensive, whereas ranking is cheap. This may not be true in reality in certain cases where ranking may be moderately expensive. In such situations, based on total cost considerations, k-tuple ranked set sampling is known to be a viable alternative, where one selects k units (instead of one) from each ranked set. In this article, we consider estimation of the distribution function based on k-tuple ranked set samples when the cost of selecting and ranking units is not ignorable. We investigate estimation both in the balanced and unbalanced data case. Properties of the estimation procedure in the presence of ranking error are also investigated. Results of simulation studies as well as an application to a real data set are presented to illustrate some of the theoretical findings.     

Constrained Bayes and empirical Bayes estimation under random effects normal ANOVA model with balanced loss function

The paper develops constrained Bayes and empirical Bayes estimators in the random effects ANOVA model under balanced loss functions. In the balanced normal–normal model, estimators of the Bayes risks of the constrained Bayes and constrained empirical Bayes estimators are provided which are correct asymptotically up to O(m^-1)$\mathrm{O}(m^{-1})$, that is the remainder term is o(m^-1)$\mathrm{o}(m^{-1})$, m$m$ denoting the number of strata.     

Some new factor screening designs using the search linear model

Factor screening designs for searching two and three effective factors using the search linear model are discussed. The construction of such factor screening designs involved finding a fraction with small number of treatments of a 2^m factorial experiment having the property P_2t (no 2t columns are linearly dependent) for t=2 and 3. A ‘Packing Problem’ is introduced in this connection. A complete solution of the problem in one case and partial solutions for the other cases are presented. Many practically useful new designs are listed.     

LGBTQ Activist Organizations as ‘Respectably Queer’ in India: Contesting a Western View

This study contests the distinction of LGBTQ (lesbian, gay, bisexual, transgender and queer) organizations suggested by earlier scholars as ‘respectable’ — i.e. normalizing, professionalizing and conforming to the dominant cultural and institutional patterns — and ‘queer’, meaning challenging the cultural and institutional forces that ‘normalize and commodify differences’. Using Bernstein's model of identity deployment, it is found problematic to distinguish LGBTQ organizations this way because when the actions of LGBTQ organizations are more complex to describe, it is not warranted to conflate identity goals with identity strategies — whether normalizing (respectable) or differentiating (queer). To examine these concerns, a qualitative inquiry was used to study five LGBTQ organizations in India where the intersections of post‐colonial ethnicity, gender, social class and sexuality offer an intriguing context through which to study queer activism. Based on the findings, it is argued from a post‐colonial perspective that when the socio‐cultural and historical existence of non‐homonormative queer communities and practices is strong, LGBTQ organizations challenge the heteronormative and/or other forms of domination to become ‘queer’. But they may simultaneously become ‘respectable′ by conforming to the diversity politics of non‐profit business, donors, and social movement organizations they seek support from, and turn out as ‘respectably queer’.     

Bayesian Variable Selection Under Collinearity

In this article, we highlight some interesting facts about Bayesian variable selection methods for linear regression models in settings where the design matrix exhibits strong collinearity. We first demonstrate via real data analysis and simulation studies that summaries of the posterior distribution based on marginal and joint distributions may give conflicting results for assessing the importance of strongly correlated covariates. The natural question is which one should be used in practice. The simulation studies suggest that posterior inclusion probabilities and Bayes factors that evaluate the importance of correlated covariates jointly are more appropriate, and some priors may be more adversely affected in such a setting. To obtain a better understanding behind the phenomenon, we study some toy examples with Zellner’s g-prior. The results show that strong collinearity may lead to a multimodal posterior distribution over models, in which joint summaries are more appropriate than marginal summaries. Thus, we recommend a routine examination of the correlation matrix and calculation of the joint inclusion probabilities for correlated covariates, in addition to marginal inclusion probabilities, for assessing the importance of covariates in Bayesian variable selection.     

Negative and Positive Partial Mobility: A Study of the Relative Changes in Human Development

In this paper, we have considered the issues concerning dynamic changes in HDI and its various components from a relative standpoint. The analysis of HDI mobility should entail directional movement introduced by Fields (in Distribution and development: a new look at the developing world. MIT Press, Cambridge, 2001). However, Fields’ analysis was in the space of absolute values. Here, we will try to extend this exercise to the positional mobility index by considering the question of improvement and deterioration in relative positions. This requires the concept of partial mobility where mobility is judged from the viewpoint of a particular group. We then try to introduce directional changes in partial mobility through axiomatic framework. Finally, we provide an illustrative example from the Indian data.     

Democracy and human development: recent legislation in India

Human Development (HD) requires that development must accompany fundamental human concerns that make life worth living. It is surprising that despite being a democracy, India performs poorly on HD. In this backdrop, four pieces of legislation of different orientations have been passed since 1998–99: ‘Swarnajayanti Gram Swarozgar Yojana’, the ‘Right to Information’, the ‘National Rural Employment Guarantee Act’ and the ‘Right to Education’. Where successful, they have empowered the beneficiaries. Though not expressed as such, nor exclusively directed to this end, these pieces of legislation are bound together with democracy's demand for HD: they are influenced externally by various aspects of globalisation; internally, development is continuously interrogated by democracy, competitive politics and social activism.