Classical network-formation games (NFGs) are played on directed graphs, and are used in network design and analysis. Edges in the network are associated with costs and players have reachability objectives, which they try to fulfill at a minimal cost. When several players use the same edge, they share its cost. The theoretical and practical aspects of NFGs have been extensively studied and are w...

This research develops the notion of environmental fit and flexibility and illustrates the importance of such fit empirically using survey data from 101 manufacturing firms. Two dimensions of environmental dynamism are identified and the fit between them and different approaches to flexibility are assessed. Hierarchical regressions provide evidence that flexibility is a stronger predictor of pe...

Empirical Bayes approach is an attractive method for estimating hyperparameters in hierarchical models. But, under the assumption of normality for a multi-level heteroscedastic hierarchical model, which involves several explanatory variables, the analyst may often wonder whether the shrinkage estimators have efficient asymptotic properties in spite of the fact they involve numerous hyperparamet...

Ecologists often seek to understand patterns and processes across multiple spatial and temporal scales ranging from centimeters to hundreds of meters and from seconds to years. Hierarchical statistical models offer a framework for sampling design and analysis that can be used to incorporate the information collected at finer scales while allowing comparison at coarser scales. In this study we u...

We show that prediction of travel time on a 28-km long highway section based on on-line travel time measurements with video is practicable by data mining and neuro-fuzzy methods. We introduce two new prediction models. The first one is a result of GUHA style data mining analysis and Total Fuzzy Similarity method, and the second one is a hierarchical model based on neuro-fuzzy modelling. Compari...

We study closures of hierarchical models which are exponential families associated with hypergraphs by decomposing the corresponding interaction spaces in a natural and transparent way. Here, we apply general results on closures of exponential families. Index Terms – Closure of exponential family, graphical model, hierarchical model, interaction order.

In this paper, a Bayesian hierarchical model is used to anaylze the female breast cancer mortality rates for the State of Missouri from 1969 through 2001. The logit transformations of the mortality rates are assumed to be linear over the time with additive spatial and age effects as intercepts and slopes. Objective priors of the hierarchical model are explored. The Bayesian estimates are quite ...

This paper describes the results of current research into an artificial nervous system for animats, a class of robots based on animals. The system is based on a hierarchical model and has been implemented using evolutionary artificial neural networks. A new neuron model has been developed for use in the system. The artificial neural networks are combined in a flexible manner to create central p...

Network distance is an important parameter in optimizing performance of network applications. Although there are a number of network distance prediction mechanisms, they all take no consideration of Internet structure, which has great influence on Internet distance characteristics. By analyzing the hierarchical structure feature of Internet, a hierarchical network distance predication mechanism...