is also an important concept in the context of stochastic dynamics. For example, some processes may follow a random walk, given in discrete time as where is an i.i.d. error term. This equation has a unit root (a value of 1 for the eigenvalue of its characteristic equation), and hence exhibits marginal stability, so special time series techniques must be used in empirically modeling a system containing such an equation. Marginally stable Markov processes are those that possess null recurrent classes. See also Lyapunov stability Exponential stability References Dynamical systems Stability theory