MONTE CARLO AND LATIN HYPERCUBE METHODS THROUGH A CASE STUDY

摘要

Monte Carlo and Latin Hypercube methods are two famous computational algorithms for simulating some problems with significant stochasticity. The main dif-ference between them is the Latin Hypercube method takes into account the full coverage sampling. In this work, both methods are compared via a real example, the study of one apple quality attribute called the solu-ble solids content.