Identifying ergodicity breaking for fractional anomalous diffusion: Criteria for minimal trajectory length

Phys Rev E. 2016 Nov;94(5-1):052136. doi: 10.1103/PhysRevE.94.052136. Epub 2016 Nov 22.

Abstract

In this paper, we study ergodic properties of α-stable autoregressive fractionally integrated moving average (ARFIMA) processes which form a large class of anomalous diffusions. A crucial practical question is how long trajectories one needs to observe in an experiment in order to claim that the analyzed data are ergodic or not. This will be solved by checking the asymptotic convergence to 0 of the empirical estimator F(n) for the dynamical functional D(n) defined as a Fourier transform of the n-lag increments of the ARFIMA process. Moreover, we introduce more flexible concept of the ε-ergodicity.