Superstatistical analysis and modelling of heterogeneous random walks.

ABSTRACT: Stochastic time series are ubiquitous in nature. In particular, random walks with time-varying statistical properties are found in many scientific disciplines. Here we present a superstatistical approach to analyse and model such heterogeneous random walks. The time-dependent statistical parameters can be extracted from measured random walk trajectories with a Bayesian method of sequential inference. The distributions and correlations of these parameters reveal subtle features of the random process that are not captured by conventional measures, such as the mean-squared displacement or the step width distribution. We apply our new approach to migration trajectories of tumour cells in two and three dimensions, and demonstrate the superior ability of the superstatistical method to discrimina

SUBMITTER: Metzner C 

PROVIDER: S-EPMC4491834 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature