set.seed(0)
Print(RFoptions())
## a very toy example to understand the use
model <- RRdistr(norm())
v <- 0.5
Print(RFdistr(model=model, x=v), dnorm(x=v))
Print(RFdistr(model=model, q=v), pnorm(q=v))
Print(RFdistr(model=model, p=v), qnorm(p=v))
n <- 10
set.seed(10); r <- RFdistr(model=model, n=n)
set.seed(10); Print(r, rnorm(n=n))
## note that a conditional covarianc function given the
## random parameters is given
model <- RMgauss(scale=exp())
for (i in 1:3) {
readline(paste("Simulation no.", i, ": press return", sep=""))
plot(model)
plot(RFsimulate(model, x=seq(0,10,0.1)))
}
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