RandomFields (version 3.0.10)

GaussianFields: Methods for Gaussian Random Fields

Description

Hier all the methods (models) for simulating Gaussian random fields are listed

Implemented models

ll{ RPcirculant simulation by circulant embedding RPcutoff simulation by a variant of circulant embedding RPcoins simulation by random coin / shot noise RPgauss generic model that chooses automatically among the specific methods RPhyperplane simulation by hyperplane tessellation RPintrinsic simulation by a variant of circulant embedding RPnugget simulation of (anisotropic) nugget effects RPsequential sequential method RPspecific model specific methods (very advanced) RPspectral spectral method RPtbm turning bands }

References

• Chiles, J.-P. and Delfiner, P. (1999)Geostatistics. Modeling Spatial Uncertainty.New York: Wiley. % \item Gneiting, T. and Schlather, M. (2004) % Statistical modeling with covariance functions. % \emph{In preparation.}
• Schlather, M. (1999)An introduction to positive definite functions and to unconditional simulation of random fields.Technical report ST 99-10, Dept. of Maths and Statistics, Lancaster University.
• Schlather, M. (2010) On some covariance models based on normal scale mixtures.Bernoulli,16, 780-797.
• Schlather, M. (2011) Construction of covariance functions and unconditional simulation of random fields. In Porcu, E., Montero, J.M. and Schlather, M.,Space-Time Processes and Challenges Related to Environmental Problems.New York: Springer. % \item Schlather, M. (2002) Models for stationary max-stable % random fields. \emph{Extremes} \bold{5}, 33-44.
• Yaglom, A.M. (1987)Correlation Theory of Stationary and Related Random Functions I, Basic Results.New York: Springer.
• Wackernagel, H. (2003)Multivariate Geostatistics.Berlin: Springer, 3nd edition.

See Also

RP, Other models, RMmodel, RFsimulateAdvanced

Examples

RFoptions(seed=0)

RFoptions(printlevel=4)
x <- seq(0, 10, 0.01)
z <- RFsimulate(RMexp(), x) # circulant embedding is chosen
RFoptions(seed=NA)