Pykov implements the computation of some of the most common quantities related to discrete-time finite regular Markov Chains, namely: steady state, mean first p

Pykov implements the computation of some of the most common quantities related to discrete-time finite regular Markov Chains, namely: steady state, mean first passage times and absorbing times. The calculation are performed by means of the analytic formulas described on Kemeny&Snell, and the steady state is derived with the inverse iteration method. If you are interested on random walkers, pykov offers a handy way to generate them and evaluate their probability. Sorry, I do not know PyMC well enough to say if the above quantities can be calculated also with it.