![]() For example, dynamic memory allocation is used for all internal variables and hence there are no pre-determined dimensions. The re-coding hones close to the original FORTRAN code, but allows for significantly more flexibility. The LHS utility described herein is a full re-coding using C/C++ of the original LHS utility-developed at Sandia National Labs (Swiler and Wyss (2004)), written in FORTRAN and freely available. ![]() The LHS utility, for which this document describes the usage, also allows for user-specified correlations between two or more of the sampled distributions. ![]() Latin Hypercube Sampling (LHS) is one method of Monte Carlo-type sampling, which is useful for limiting sample size yet maximizing the range of sampling of the underlying distributions. "A Summary Guide to the Latin Hypercube Sampling (LHS) Utility" ![]()
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