Stephen R. Carpenter

This paper introduces Euler and Hermite reconstruction methods to estimate Langevin systems from time series data, showing their effectiveness across simulated and real ecological and climate datasets.

The paper shows that stochastic regimes can obscure attractors in data, and that reconstruction algorithms can reveal them by analyzing the relationship between noise and system equilibria.