payoffs depend on the social distance between them. We characterize the clustering coefficient and average path length in … distributions, positive assortativity of degrees, and clustering-degree correlation. …

clustering approach used for the analysis is useful in an inferential framework. The segments built starting from the …

equity of pure premium, as required by insurance regulation. To achieve this goal, the spatially-constrained clustering of … the design of geographical rating territories, a clustering approach based on Delaunay triangulation is proposed …-constrained clustering approach in defining geographical rating territories for insurance rate regulation purposes. The significance of this …

The goal of the paper is to present the framework for combining clustering and classification for churn management in … approach to churn management using clustering and classification, which was tested on the churn dataset with a rich variable …

Purpose: This study proposes a new two-stage clustering method to break down the symmetric multiple traveling salesman …-programming model. A comparison with the k-means++ clustering algorithm, one of the most popular clustering algorithms, was made to … study tackles the issue of improving the performance of clustering-based optimization approaches in solving the mTSP by …

This paper investigates the clustering or dependency of extremes in financial returns by estimating the extremal index … value, in which smaller values of the extremal index correspond to more clustering. We apply the interval estimator method … results show that clustering occurs in the emerging and developed markets under several threshold values. This study will shed …