Latin Hypercube Sampling of Gaussian Random Fields

Abstract

Following the method of Stein, this article shows how a Latin hypercube sample can be drawn from a Gaussian random field. In a case study the efficiency of Latin hypercube sampling is compared experimentally to that of simple random sampling. The model outputs studied are the mean and the 5- and 95-percentile of the areal fraction where point concentration of zinc in the topsoil exceeds a given threshold. The Latin hypercube sampling procedure slightly distorts the short-distance correlation, and in an artificial example, it is shown that this distortion is modest for small samples and vanishes for large samples.

KEY WORDS:

• Environmental model
• Geostatistical simulation
• Monte Carlo
• Risk analysis
• Uncertainty analysis