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Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
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Stationarity of the inter-event power-law distributions
Yerali Gandica1, João Carvalho2, Fernando Sampaio Dos Aidos2
1Department of Mathematics and Namur Center for Complex Systems-naXys, University of Namur, Namur, Belgium.
Abstract:
A number of human activities exhibit a bursty pattern, namely periods of very high activity that are followed by rest periods. Records of these processes generate time series of events whose inter-event times follow a probability distribution that displays a fat tail. The grounds for such phenomenon are not yet clearly understood. In the present work we use the freely available Wikipedia's editing records to unravel some features of this phenomenon. We show that even though the probability to start editing is conditioned by the circadian 24 hour cycle, the conditional probability for the time interval between successive edits at a given time of the day is independent from the latter. We confirm our findings with the activity of posting on the social network Twitter. Our results suggest that there is an intrinsic humankind scheduling pattern: after overcoming the encumbrance of starting an activity, there is a robust distribution of new related actions, which does not depend on the time of day at which the activity started.
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