sim.rf: Simulates a random field

Description

Simulates a random Gaussian field on a regular grid.

Usage

sim.rf(obj,...)

Arguments

obj

A covariance object that includes information about the covariance function and the grid for evaluation. Usually this created by a setup call to exp.image.cov. (See details below.)

...

Additional arguments passed to a particular method.

Value

A matrix with the random field values

Details

This function takes an object that includes some preliminary calculations and so is more efficient for simulating more than one field from the same covariance. However, the algorithm using a 2-d FFT may not always if the correlation scale is large (See the FIELDS manual for more details.) For a stationary model the covariance object has the components:

names( obj) "m" "n" "grid" "N" "M" "wght"

. where m and n are the number of grid points in x and y grid is a list with the grid point values for x and y N and M is the size of the larger grid that is used for simulation ( usually M= 2*m and N=2*n) to minimize periodic effects. wght is a matrix from the FFT of the covariance function. The easiest way to create this object is to use for example exp.image.cov with setup=T ( see below). To create the object for the wavelet model see W.image.cov with setup=T. The FIELDS manual has more information about this function.

Examples

Run this code

#Simulate a Gaussian random field with an exponential covariance function,  
#range parameter = 2.0 and the domain is  [0,5]X [0,5] evaluating the 
#field at a 100X100 grid.  
grid<- list( x= seq( 0,5,,100), y= seq(0,5,,100)) 
obj<-exp.image.cov( grid=grid, theta=.5, setup=TRUE)
look<- sim.rf( obj)
# Now simulate another ... 
look2<- sim.rf( obj)
# take a look 
# set.panel(2,1)
# image.plot( grid$x, grid$y, look) 
# image.plot( grid$x, grid$y, look2)