papers.GSPSJ06: Fast and Exact Simulation of Large Gaussian Lattice Systems... In RandomFields: Simulation and Analysis of Random Fields

Description

Here, the code of the paper on ‘Fast and Exact Simulation of Large Gaussian Lattice Systems in R2’ is given.

References

• Gneiting, T., Sevcikova, H., Percival, D.B., Schlather, M., Jiang, Y. (2006) Fast and Exact Simulation of Large Gaussian Lattice Systems in R2: Exploring the Limits. J. Comput. Graph. Stat., 15, 483-501.

Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30``` ```RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set ## RFoptions(seed=NA) to make them all random again ## Figure 1 (pretty time consuming) stabletest <- function(alpha, theta, size=512) { RFoptions(trials=1, tolIm = 1e-8, tolRe=0, force = FALSE, useprimes=TRUE, strategy=0, skipchecks=!FALSE, storing=TRUE) model <- RMcutoff(diameter=theta, a=1, RMstable(alpha=alpha)) RFcov(dist=0, model=model, dim=2, seed=0) r <- RFgetModelInfo(modelname="RMcutoff", level=3)\$storage\$R_theor x <- seq(0, r, by= r / (size - 1)) * theta err <- try(RFsimulate(x, x, model=RPcirculant(model), n=0)) return(if (class(err) == "try-error") NA else r) } alphas <- seq(1.52, 2.0, 0.02) thetas <- seq(0.05, 3.5, 0.05) m <- matrix(NA, nrow=length(thetas), ncol=length(alphas)) for (it in 1:length(thetas)) { theta <- thetas[it] for (ia in 1:length(alphas)) { alpha <- alphas[ia] cat("alpha=", alpha, "theta=", theta,"\n") m[it, ia] <- stabletest(alpha=alpha, theta=theta) if (is.na(m[it, ia])) break } if (any(is.finite(m))) image(thetas, alphas, m, col=rainbow(100)) } ```

RandomFields documentation built on Jan. 19, 2022, 1:06 a.m.