Re: monte carlo simulation
I have been thinking about the question for a while, still not quite sure what other simulation methods you referred to.
So I'm going to give you a rough idea of Monte Carlo method.
Monte Carlo simulation method is the simulation that involves random sampling. It can be used to approximate both deterministic or stochastic values, such as integration, error probability.
It is different from "deterministic" simulations (the ones that you create mathematical model and when injecting some inputs you know exactly the output ) in the way that it randomly samples input values and approximates the desired outputs using stochastic convergence due to the law of large numbers.
For example, if we want to calculate the value of an integration, instead of using numerical method like trapezoidal, we can approximate it using average of the random samples.
Code:
I = integrate x from a to b of g(x)
can be approximated by
(b-a)*1/N * {sum i from 1 to N of g(Xi) }
where Xi are the values randomly selected between a and b in a
uniform fashion
Monte Carlo is used to approximate nonrandom values to avoid heavy computation. It is also used in stochastic systems such as finding some probability or some expected values. Ulam invented the method when he was trying to find out the chance that a solitaire card game will play out successfully.