Eur. Phys. J. B (2016) 89: 50
https://doi.org/10.1140/epjb/e2016-60926-8

Regular Article

A stochastic evolutionary model generating a mixture of exponential distributions

Department of Computer Science and Information Systems, Birkbeck, University of London, London WC1E 7HX, UK

^a e-mail: mlevene@dcs.bbk.ac.uk

Received: 30 November 2015
Received in final form: 14 January 2016
Published online: 17 February 2016

Abstract

Recent interest in human dynamics has stimulated the investigation of the stochastic processes that explain human behaviour in various contexts, such as mobile phone networks and social media. In this paper, we extend the stochastic urn-based model proposed in [T. Fenner, M. Levene, G. Loizou, J. Stat. Mech. 2015, P08015 (2015)] so that it can generate mixture models, in particular, a mixture of exponential distributions. The model is designed to capture the dynamics of survival analysis, traditionally employed in clinical trials, reliability analysis in engineering, and more recently in the analysis of large data sets recording human dynamics. The mixture modelling approach, which is relatively simple and well understood, is very effective in capturing heterogeneity in data. We provide empirical evidence for the validity of the model, using a data set of popular search engine queries collected over a period of 114 months. We show that the survival function of these queries is closely matched by the exponential mixture solution for our model.