An efficient sampling scheme: Updated Latin Hypercube Sampling

Abstract An efficient sampling scheme called Updated Latin Hypercube Sampling is presented. The proposed method is an improved variant of Latin Hypercube Sampling. It uses specially modified tables of independent random permutations of rank numbers which form the strategy of generating input samples for a simulation procedure. The method is presented in order to obtain these specially modified tables. The aim of this paper is to compare estimates of certain widely used statistical parameters obtained by Updated Latin Hypercube Sampling, Latin Hypercube Sampling and Simple Random Sampling. It is shown that Updated Latin Hypercube Sampling usually results in a substantial decrease of the variance in the estimates of commonly used statistical parameters and that the bias is quite small for a moderate number of simulations. This sampling technique seems to be generally very useful, efficient and superior to other methods especially in the case of statistical, sensitivity and probability analyses of complex analytical models with random input variables.