Use Latin Hypercube sampling when you are concerned primarily with the accuracy of the simulation statistics. The added expense of this method is the extra memory required to hold the full sample for each assumption while the simulation runs. It uses a technique known as 'stratified sampling without replacement' ( Iman et al. In fact, we would say that it is one of the features that is essential in any risk analysis software package. Thus, with Latin Hyper-cube sampling, you do not need as many trials to achieve the same statistical accuracy as with Monte Carlo sampling. Latin Hypercube sampling, or LHS, is an option that is now available for most risk analysis simulation software programs. Latin Hypercube sampling is generally more precise than conventional Monte Carlo sampling when calculating simulation statistics, because the entire range of the distribution is sampled more evenly and consistently. After Crystal Ball® uses all the values from the sample, it generates a new batch of values. ![]() The collection of values forms the Latin Hypercube sample. The sample values are randomly shuffled among different variables. ![]() The basic of Latin Hypercube sampling is a full stratification of sampled distribution with a random selection inside each stratum. Crystal Ball® then selects a random assumption value for each segment according to the segment's probability distribution. Discrete Latin Hypercube Design The original Latin Hypercube sampling is developed as a variance reduction technique or as a screening technique. ![]() With Latin Hypercube sampling, Crystal Ball® divides each assumption's probability distribution into non-overlapping segments, each having equal probability. The original Latin Hypercube sampling is developed as a variance reduction technique or as a screening technique.
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