A stochastic evolutionary model for capturing human dynamics
作者： Trevor Fenner , Mark Levene , George Loizou
DOI: 10.1088/1742-5468/2015/08/P08015
关键词: Population 、 Theoretical computer science 、 Survival function 、 Human dynamics 、 Mathematics 、 Reliability (computer networking) 、 Stochastic process 、 Range (mathematics) 、 Generative model 、 Econometrics 、 Set (abstract data type)
摘要: The recent interest in human dynamics has led researchers to investigate the stochastic processes that explain behaviour various contexts. Here we propose a generative model capture of survival analysis, traditionally employed clinical trials and reliability analysis engineering. We derive general solution for form product, then continuous approximation via renewal equation describing age-structured population dynamics. This enables us wide range distributions, according choice mortality distribution. provide empirical evidence validity from longitudinal data set popular search engine queries over 114 months, showing function these is closely matched by our with power-law mortality.
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