 Latin hypercube sampling

Latin hypercube sampling (LHS) is a statistical method used to generate a sample of plausible combinations of parameters from a multidimensional distribution. It is particularly useful in the context of uncertainty analysis and simulation studies where one needs to efficiently sample from multiple input variables. ### Key Characteristics of Latin Hypercube Sampling: 1. **Stratified Sampling**: LHS divides each dimension (input variable) into equally sized intervals (strata) and ensures that each interval is sampled exactly once.