Emergence of scaling in random networks
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Systems as diverse as genetic networks or the world wide web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This feature is found to be a consequence of the two generic mechanisms that networks expand continuously by the addition of new vertices, and new vertices attach preferentially to already well connected sites. A model based on these two ingredients reproduces the observed stationary scale-free distributions, indicating that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
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Formalization of the generalized Pareto principle and structural typicality of the 20/80-rule
A formalization of the generalized Pareto principle derives that exponential and normal distributions with 100 to 100,000 samples produce p values near 0.2, close to the 80/20 rule and below prior saturation conjectures.
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