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RMintrinsic

Intrinsic Embedding Covariance Model


Description

RMintrinsic is a univariate stationary isotropic covariance model which depends on a univariate stationary isotropic covariance model.

The corresponding covariance function C of the model only depends on the distance r ≥ 0 between two points and is given by

C(r)=a_0 + a_2 r^2 + φ(r), 0≤ r ≤ diameter

C(r)=b_0 (rawR D - r)^3/(r), diameter ≤ r ≤ rawR * diameter

C(r) = 0, rawR * diameter ≤ r

Usage

RMintrinsic(phi, diameter, rawR, var, scale, Aniso, proj)

Arguments

phi

an RMmodel; has to be stationary and isotropic

diameter

a numerical value; positive; should be the diameter of the domain on which simulation is done

rawR

a numerical value; greater or equal to 1

var,scale,Aniso,proj

optional arguments; same meaning for any RMmodel. If not passed, the above covariance function remains unmodified.

Details

The parameters a_0, a_2 and b_0 are chosen internally such that C becomes a smooth function. See formulas (3.8)-(3.10) in Gneiting et alii (2006). This model corresponds to the method Intrinsic Embedding. See also RPintrinsic.

NOTE: The algorithm that checks the given parameters knows only about some few necessary conditions. Hence it is not ensured that the Stein-model is a valid covariance function for any choice of φ and the parameters.

For certain models phi, i.e. stable, whittle, gencauchy, and the variogram model fractalB some sufficient conditions are known.

Value

RMintrinsic returns an object of class RMmodel.

Author(s)

References

  • Gneiting, T., Sevecikova, H, Percival, D.B., Schlather M., Jiang Y. (2006) Fast and Exact Simulation of Large Gaussian Lattice Systems in $R^2$: Exploring the Limits. J. Comput. Graph. Stat. 15, 483–501.

  • Stein, M.L. (2002) Fast and exact simulation of fractional Brownian surfaces. J. Comput. Graph. Statist. 11, 587–599

See Also

Examples

RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
##                   RFoptions(seed=NA) to make them all random again

x.max <- 10
model <- RMintrinsic(RMfbm(alpha=1), diameter=x.max)
x <- seq(0, x.max, 0.02)
plot(model)
plot(RFsimulate(model, x=x))

RandomFields

Simulation and Analysis of Random Fields

v3.3.10
GPL (>= 3)
Authors
Martin Schlather [aut, cre], Alexander Malinowski [aut], Marco Oesting [aut], Daphne Boecker [aut], Kirstin Strokorb [aut], Sebastian Engelke [aut], Johannes Martini [aut], Felix Ballani [aut], Olga Moreva [aut], Jonas Auel[ctr], Peter Menck [ctr], Sebastian Gross [ctr], Ulrike Ober [ctb], Paulo Ribeiro [ctb], Brian D. Ripley [ctb], Richard Singleton [ctb], Ben Pfaff [ctb], R Core Team [ctb]
Initial release

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