The definition carries over straightforwardly to continuous variables, where π becomes a probability density, and P (s ′, s) a transition kernel probability density from state s ′ to state s : π π ( s ′ ) P ( s ′ , s ) = π π ( s ) P ( s , s ′ ) . The detailed balance condition is stronger than that required merely for a stationary distribution, because there are Markov processes with stationary distributions that do not have detailed balance.