sim.rf {fields} | R Documentation |
Simulates a random Gaussian field on a regular grid.
sim.rf(obj,...)
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. |
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.
A matrix with the random field values
W.image.cov, exp.image.cov, sim.rf.W
#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)