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\name{RRmcmc}
\alias{RRmcmc}
\title{Random Sample From The Modulus Of A Function}
\description{
\command{RRmcmc} draws a random sample from the
modulus of any given function (provided the integral is finite).
}
\usage{
RRmcmc(phi, mcmc_n, sigma, normed, maxdensity, rand.loc, gibbs)
}
\arguments{
\item{phi}{an arbitrary integrable function
}
\item{mcmc_n}{
positive integer. Every \code{mcmc_n}th element of the MCMC chain
is returned.
}
\item{sigma}{positive real number.
The MCMC update is done by adding a normal variable with
standard deviation \code{sigma}.
}
\item{normed}{logical.
Only used if the value of the density is calculated.
If \code{FALSE} the unnormed value given by \code{phi} is returned.
Default: \code{FALSE}.
}
\item{maxdensity}{positive real number.
The given density is truncated at \code{maxdensity}.
Default: 1000.
}
\item{rand.loc}{logical. Internal. Do not change the value.
Default: \code{FALSE}.
}
\item{gibbs}{logical. If \code{TRUE} only one component is updated at a
time.
Default: \code{FALSE}.
}
}
\value{
\command{\link{RRmcmc}} returns an object of class \code{\link[=RMmodel-class]{RMmodel}}.
}
\note{
The use of \command{RRmcmc} is completely on the risk of the user. There is no
way to check whether the integral of the modulus is finite.
}
\me
\seealso{
\command{\link{RMmodel}},
\link{RR},
\command{\link{RRdistr}},
\command{\link{RMuser}}.
}
\examples{\dontshow{StartExample()}
RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
## RFoptions(seed=NA) to make them all random again
## here a model with random scale parameter
## not exponential, but the Laplace distribution as symmetry is assumed
z <- RFrdistr(RRmcmc(RMexp(), sigma=1), n=10000, cores=1)
hist(z, 100, freq=FALSE)
curve(0.5 * exp(-abs(x)), add=TRUE, col="blue") ## Laplace distribution
\dontshow{FinalizeExample()}}
\keyword{spatial}
\keyword{models}
|
