Statistical tests for validating geostatistical simulation algorithms
Computers & Geosciences
A turning bands program for conditional co-simulation of cross-correlated Gaussian random fields
Computers & Geosciences
Change-of-support models and computer programs for direct block-support simulation
Computers & Geosciences
A computer package for modeling and simulating regionalized count variables
Computers & Geosciences
Truncated Gaussian simulation of discrete-valued, ordinal coregionalized variables
Computers & Geosciences
An enhanced Gibbs sampler algorithm for non-conditional simulation of Gaussian random vectors
Computers & Geosciences
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The simulation of spatially correlated Gaussian random fields is widespread in geologic, hydrologic and environmental applications for characterizing the uncertainty about the unsampled values of regionalized attributes. In this respect, the turning bands method has received attention among practitioners, for it allows multidimensional simulations to be generated at the CPU cost of one-dimensional simulations. This work provides and documents a set of computer programs for (i) constructing three-dimensional realizations of stationary and intrinsic Gaussian random fields, (ii) conditioning these realizations to a set of data and (iii) back-transforming the Gaussian values to the original attribute units. Such programs can deal with simulations over large domains and handle anisotropic and nested covariance models. The quality of the proposed programs is examined through an example consisting of a non-conditional simulation of a spherical covariance model. The artifact banding in the simulated maps is shown to be negligible when thousands of lines are used. The main parameters of the univariate and bivariate distributions, as well as their expected ergodic fluctuations, also prove to be accurately reproduced.