RPdirect: Methods relying on square roots of the covariance matrix
In RandomFields: Simulation and Analysis of Random Fields

Description Usage Arguments Details Value References See Also Examples

Methods relying on square roots of the covariance matrix

1	RPdirect(phi, boxcox)

`phi`	object of class `RMmodel`; specifies the covariance model to be simulated.
`boxcox`	the one or two parameters of the box cox transformation. If not given, the globally defined parameters are used. See `RFboxcox` for details.

RPdirect is based on the well-known method for simulating any multivariate Gaussian distribution, using the square root of the covariance matrix. The method is pretty slow and limited to about 12000 points, i.e. a 20x20x20 grid in three dimensions. This implementation can use the Cholesky decomposition and the singular value decomposition. It allows for arbitrary points and arbitrary grids.

RPdirect returns an object of class RMmodel.

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.

Gaussian, RP, RPsequential.

RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
##                   RFoptions(seed=NA) to make them all random again
model <- RMgauss(var=10, s=10) + RMnugget(var=0.01)
plot(model, xlim=c(-25, 25))

z <- RFsimulate(model=RPdirect(model), 0:10, 0:10, n=4)
plot(z)