Stochastic Simulation: Latin Hypercube Sampling and Quasi Monte Carlo

This lecture covers Latin Hypercube Sampling (LHS) and Quasi Monte Carlo sampling (QMC) methods for stochastic simulation. It explains the goal of stratification and generating independent permutations, as well as the design of stratified random permutations. The instructor discusses algorithms for generating independent permutations and the importance of stratification in simulation. The lecture also delves into the process of constructing a design using random permutations and the concept of stratification in sampling. Various techniques for generating independent permutations and their applications in simulation are explored.