A mere hyperbolic law, like the Zipf's law power function, is often inadequate to describe rank-size relationships. An alternative theoretical distribution is proposed based on theoretical physics arguments starting from the Yule-Simon distribution. A modeling is proposed leading to a universal form. A theoretical suggestion for the "best (or optimal) distribution", is provided through an entropy argument. The ranking of areas through the number of cities in various countries and some sport competition ranking serves for the present illustrations.
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Chaos
August 2022
UrbanNet Lab, College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.
Cities are typical dynamic complex systems that connect people and facilitate interactions. Revealing general collective patterns behind spatiotemporal interactions between residents is crucial for various urban studies, of which we are still lacking a comprehensive understanding. Massive cellphone data enable us to construct interaction networks based on spatiotemporal co-occurrence of individuals.
View Article and Find Full Text PDFPLoS One
June 2017
University of Macerata, Department of Economics and Law, Via Crescimbeni 20, I-62100, Macerata, Italy.
A mere hyperbolic law, like the Zipf's law power function, is often inadequate to describe rank-size relationships. An alternative theoretical distribution is proposed based on theoretical physics arguments starting from the Yule-Simon distribution. A modeling is proposed leading to a universal form.
View Article and Find Full Text PDFPhys Rev E Stat Nonlin Soft Matter Phys
April 2014
Department of Physics, Faculty of Science and Engineering, Chuo University, Kasuga 1-chome, Bunkyo, Tokyo, Japan.
We propose a stochastic model of Zipf's law, namely a power-law relation between rank and size, and clarify as to why a specific value of its power-law exponent is quite universal. We focus on the successive total of a multiplicative stochastic process. By employing properties of a well-known stochastic process, we concisely show that the successive total follows a stationary power-law distribution, which is directly related to Zipf's law.
View Article and Find Full Text PDFNature
November 2006
Centre for Advanced Spatial Analysis, The Bartlett School, University College London, 1-19 Torrington Place, London WC1E 6BT, UK.
Many objects and events, such as cities, firms and internet hubs, scale with size in the upper tails of their distributions. Despite intense interest in using power laws to characterize such distributions, most analyses have been concerned with observations at a single instant of time, with little analysis of objects or events that change in size through time (notwithstanding some significant exceptions). It is now clear that the evident macro-stability in such distributions at different times can mask a volatile and often turbulent micro-dynamics, in which objects can change their position or rank-order rapidly while their aggregate distribution appears quite stable.
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