Markov Chains Explained Visually (2014)
Is there a standard way to build markov chains with deeper memory than just the current state? For example in the rainy sunny markov chain our rainy probability should/could  decrease as the number of rainy days in a row increases. In a pure state machine this would require an infinite number of states for SS...SSS and RR...RRR.