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Im currently researching into stochastic proesses. The gaussian process wasnt hard to tackle, However, I dont understand the Markov process. See I understand that a stochastic process is a family of random variable's which is dependent and distinguished upon another variable. But with a Markov process I cant see where this family of random variables like the way I see it in the Gaussian process. How could I understand this graphically?

I also realise that we need to sets of information, is it the initial distribution or the initial point and the transition probability?

Another thing I dont understand is if these stochastic processes are related to time how are we suppose to know the distribution at a particular point in time if only one thing can occur at a particular point in time?

Please help,

Regards

Steven