Dive into Stochastic Modeling | Markov Chain
A stochastic modeling is a tool which allows randomness within it's system. A Markov chain is a mathematical system that experiences transitions from one state to another. T he probability of transitioning to any particular state is dependent solely on the current state and time elapsed. A Markov chain is a stochastic process, but it differs from a general stochastic process in that a Markov chain must be "memory-less." That is, (the probability of) future actions are not dependent upon the steps that led up to the present state. This is called the Markov property. The initial probabilities for the creation of transition matrix are obtained based on the historical data with sequence(transitions and not the pure data). Since, is a stochastic process - the change/transition is a core assumption. Since, the process is dependent on the current state, the initial vector for N=N*A => N=N. Here, A is considered to be 1, in other words at the time of start the information p...