Description Usage Arguments Details Value See Also Examples
Through RRdistr
distribution families can be passed to RandomFields to create distributions available
in the RMmodel
definitions.
1 2 3 4 5 |
model,params |
an |
x |
the location where the density is evaluated |
q |
the location where the probability function is evaluated |
p |
the value where the quantile function is evaluated |
n |
the number of random values to be drawn |
dim |
the dimension of the vector to be drawn |
... |
for advanced use:
further options and control arguments for the simulation
that are passed to and processed by |
RFdistr
is the generic function for the 4 functions
belonging to a distribution.
as described in the arguments
RRgauss
, RR
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
## RFoptions(seed=NA) to make them all random again
## 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
r <- RFdistr(model=model, n=n, seed=0)
set.seed(0); Print(r, rnorm(n=n))
## note that a conditional covariance function given the
## random parameters is given here:
model <- RMgauss(scale=exp())
for (i in 1:3) {
RFoptions(seed = i + 10)
readline(paste("Model no.", i, ": press return", sep=""))
plot(model)
readline(paste("Simulation no.", i, ": press return", sep=""))
plot(RFsimulate(model, x=seq(0,10,0.1)))
}
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