Given letters, probabilities, and transitional probabilities, implement Markov Chain.
n number of transitions
Output: sequence of letters
Start by sampling the first entry from the prior probabilities (say X1). Then extract the X1^th row of the transition matrix and sample X2 based on the probabilities on that row (remember that transition matrices rows sum to 1). Next, extract the X2^th row of the transition matrix to sample X3 and so on.