Sampling Methods and Parallelism into Monte Carlo Simulation

This paper provides an updated review of Monte Carlo simulation. The use of random sampling, its consequences in simulation, the use of descriptive sampling, its advantages, its limits and its improvement upon the precision of simulation estimates: Refined descriptive sampling. This state of the art gives also an insight into other sampling procedures used in the literature, like Ranked set sampling, Systematic sampling, Stratified sampling, Latin hypercube sampling, L Ranked set sampling, Importance sampling and Quasi Monte Carlo methods. Finally, as a future work parallelism of the best sampling procedure is proposed to reduce the time of running simulation experiments.