title: Circular analysis in complex stochastic systems.
abstract: Ruling out observations can lead to wrong models. This danger occurs unwillingly when one selects observations, experiments, simulations or time-series based on their outcome. In stochastic processes, conditioning on the future outcome biases all local transition probabilities and makes them consistent with the selected outcome. This circular self-consistency leads to models that are inconsistent with physical reality. It is also the reason why models built solely on macroscopic observations are prone to this fallacy.
authors.affiliation: Max Planck Institute of Colloids and Interfaces, Department of Theory and Bio-Systems, Potsdam, 14424, Germany.
authors.forename: Angelo
authors.initials: A
authors.lastname: Valleriani