Two-Level Hierarchical Transportation Networks: A New Set of Problems and Practical Applications*

This paper defines and solves a set of new problems for two-level hierarchical transportation networks. Given a set of points, the objective is to find the path of a primary link such that a weighted sum of the lengths of the perpendiculars from each point to the primary link and the distance between the feet of the two extreme perpendiculars is minimized. The perpendiculars are the connecting or secondary links and the primary link could be a straight line or a curve. The paper provides an algorithm and computational results for the case in which the primary link is a straight line. Implementation approaches are also discussed.     

Estimation of variance components in an unbalanced one-way classification

In the unbalanced one-way random effects model the weighted least squares approach with estimated weights is used to develop a relatively simple estimator of variance components. As the number of classes increases, the proposed estimator is seen not only to be best asymptotically normal but also to be asymptotically equivalent to the maximum likelihood estimator.     

Ghostly Images,Phantom Discourses,and the Virtuality of the Global

The central premise of this article is that the conceptual terrain of the global is fundamentally unstable, that its content is far from determined. This opens the door to many different interpretations and uses of the term, where the referent is not so much to a pre-given reality, or even a tangible geographical space. Rather, the global constitutes its own content in the various fields in which it gets deployed, selectively affirming particular images and representations, while denying, repressing, or otherwise excluding others. I draw on the early history of film to argue that the global is a virtual distribution of value and intelligibility, where its images and signs no longer ‘represent’ an independent reality, but actually shape and transform the inter-subjective experiences of its virtual subjects. I use a recent documentary film on call centers in India to demonstrate how distinct regimes of cinematic images enable different kinds of interventions into these virtual distributions, revealing the global as a richly imagined terrain of discourses and representations, which are always already subject to re-distribution.

El argumento principal de este artículo es que en el ámbito conceptual, lo global es fundamentalmente inestable, aún falta mucho para determinar su contenido. El término global tiene muchas interpretaciones y usos variados, dado que el referente no aplica a una realidad preestablecida ni corresponde a un espacio geográfico tangible. El término global constituye su propio contenido en los diferentes campos en los cuales es utilizado, aseverando imágenes y representaciones particulares selectivas, mientras que a la vez niega, reprime, o excluye otras. Me inspiro en los comienzos de la historia del cine para argumentar que lo global es la distribución virtual del valor y de la ininteligibilidad, donde las imágenes y los letreros ya no “representan” una realidad independiente, sino que forman y transforman las experiencias inter-subjetivas de sus sujetos virtuales. Utilizo un documental fílmico reciente sobre los “call centers” de la India para demostrar cómo diferentes regímenes de imágenes fílmicas permiten diferentes tipos de intervenciones a estos distribuidores virtuales, que revelan lo global como un rico imaginario de discursos y representaciones que siempre han sido y son sujetas a una re-distribución.

     

INFERENCE IN DIRICHLET PROCESS MIXED GENERALIZED LINEAR MODELS BY USING MONTE CARLO EM

Generalized linear mixed models are widely used for describing overdispersed and correlated data. Such data arise frequently in studies involving clustered and hierarchical designs. A more flexible class of models has been developed here through the Dirichlet process mixture. An additional advantage of using such mixture models is that the observations can be grouped together on the basis of the overdispersion present in the data. This paper proposes a partial empirical Bayes method for estimating all the model parameters by adopting a version of the EM algorithm. An augmented model that helps to implement an efficient Gibbs sampling scheme, under the non‐conjugate Dirichlet process generalized linear model, generates observations from the conditional predictive distribution of unobserved random effects and provides an estimate of the average number of mixing components in the Dirichlet process mixture. A simulation study has been carried out to demonstrate the consistency of the proposed method. The approach is also applied to a study on outdoor bacteria concentration in the air and to data from 14 retrospective lung‐cancer studies.     

The impact of information and computer based training on negotiators' performance

This paper presents the results of an experiment on negotiation, designed to measure the impact of (1) computerized training and (2) information on negotiators' performanceThe paper is structured as follows. First, we review the literature on negotiation training. Second, we develop a conceptual framework to link various forms of Negotiation Support Systems to joint and individual negotiation performance. Third, we present the negotiation paradigm — a bilateral monopoly — and the computerized training system we used. Regarding training, our results show an asymmetric impact on individual performance levels and, unexpectedly, a negative impact on negotiators' joint performance. In contrast, more information improves both individual and joint performance. Finally, we discuss these results, and outline further research questions.     

Racial capitalism

Theory and Society - “Racial capitalism” has surfaced during the past few decades in projects that highlight the production of difference in tandem with the production of...     

Estimation in one–way classification with heteroscedastic error

For an unbalanced one way calssification under the random effect model the problem of estimation of the fixed effect parameter and the variance is considered. Tje error variance which are funtionally related to the above set of parameters are assumed to fall into k classes with constant error varaince for a class. The asymptotic properties of the proposed estimate is established for increasing number of classes k, assuming the number of observations in the classes form a fixed sequence