Can you chose between Monte Carlo technique simulation and Markov Chain model?
A Markov Chain is a model of how your system moves from state to state but developing it can sometimes be difficult. The basic idea is that your data will have certain states associated with it and you will move each one of them from state to state. This movement from state to state happens based on probability and you know these probabilities.
Monte Carlo techniques are estimators. Once you have a model of something, whether a Markov model or any other, you often find yourself in the position of wanting to estimate something about it. Monte Carlo techniques samples randomly and aggregates the results into an estimate of what's going to happen.
