We compute transfer entropy by estimating the invariant measure from the invariant distribution of the transfer operator approximated from time series. We use two methods for approximating the transfer operator, and find that our methods are robust to noise and show promising performance relative to other transfer entropy estimators.
We leverage the intrinsic dynamical information in empirical records to show that the external forcing of ice volume encompasses insolation signals with a wide range of orbital frequency content, and cannot be fully accounted for by a unique time series.
We review some of the ways in which causal connections can be extracted from palaeontological time series and provide an overview of three recently developed analytical frameworks that have been applied to palaeontological questions.
We use common and widespread species of planktonic foraminifera in deep-sea sediments and show that the observed global occupancy of planktonic foraminifera has been dynamically coupled to past oceanographic changes captured in deep-ocean temperature reconstructions.