RFdistr: Evaluating distribution families

Description

Through RRdistr distribution families can the passed to RandomFields to create distributions available in the RMmodel defintions

Usage

RFddistr(model, x, dim=1, ...)
RFpdistr(model, q, dim=1, ...)
RFqdistr(model, p, dim=1, ...)
RFrdistr(model, n, dim=1, ...)
RFdistr(model, x, q, p, n, dim=1, ...)

Arguments

model

an RRmodel

the location where the density is evaluated

the location there the probability function is evaluated

the value where the quantile function is evaluated

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 RFoptions

Value

as described in the arguments

Details

RFdistr is the generic function for the 4 functions belonging to a distribution.

Examples

Run this code

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)))
}
FinalizeExample()