The Go-Getter’s Guide To Markov Chain Process
Here, 1,2 and 3 are the three possible states, and the arrows pointing from one state to the other states represents the transition probabilities pij. Pt(k)=⎝⎜⎜⎜⎛P(Xt+k=1∣Xt=1)P(Xt+k=1∣Xt=2)⋮P(Xt+k=1∣Xt=n)P(Xt+k=2∣Xt=1)P(Xt+k=2∣Xt=2)⋮P(xt+k=2∣Xt=n)……⋱…P(Xt+k=n∣Xt=1)P(Xt+k=n∣Xt=2)⋮P(Xt+k=n∣Xt=n)⎠⎟⎟⎟⎞. In the hands of metereologists, ecologists, computer scientists, financial engineers and other people who need to model big phenomena, Markov chains can get to be quite large and powerful. […]