RFoptions(seed=0)
## here a model with random scale parameter
model <- RMgauss(scale=exp(rate=1))
x <- seq(0,10,0.02)
n <- if (interactive()) 10 else 1
for (i in 1:n) {
readline(paste("Simulation no.", i, ": press return", sep=""))
plot(RFsimulate(model, x=x))
}
## another possibility to define exactly the same model above is
## model <- RMgauss(scale=exp())
## note that however, the following two definitions lead
## to covariance models with fixed scale parameter:
## model <- RMgauss(scale=exp(1)) # fixed to 2.7181
## model <- RMgauss(scale=exp(x=1)) # fixed to 2.7181
## here, just two other examples:
## fst
RFoptions(seed=NA)
model <- RMmatern(nu=unif(min=0.1, max=2)) # random
for (i in 1:n) {
readline(paste("Simulation no.", i, ": press return", sep=""))
plot(RFsimulate(model, x=x))
}
## snd
## note that the fist 'exp' refers to the exponential function,
## the second to the exponential distribution.
model <- RMgauss(var=exp(3), scale=exp(rate=1))
Print(model)
plot(z <- RFsimulate(model=model, x=1:100/10))
RFoptions(seed=NA)
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