\name{lcg}
\alias{lcg}
\alias{set.lcgseed}
\alias{get.lcgseed}
\alias{runif.lcg}
\alias{rnorm.lcg}
\alias{rt.lcg}
\title{Generator for Portable Random Innovations}
\description{
Functions to generate portable random innovations.
The functions run under R and S-Plus and generate
the same sequence of random numbers. Supported
are uniform, normal and Student-t distributed
random numbers.
\cr
The functions are:
\tabular{ll}{
\code{set.lcgseed} \tab Set initial random seed, \cr
\code{get.lcgseed} \tab Get the current valus of the random seed, \cr
\code{runif.lcg} \tab Uniform linear congruational generator, \cr
\code{rnorm.lcg} \tab Normal linear congruational generator, \cr
\code{rt.lcg} \tab Student-t linear congruential generator. }
}
\usage{
set.lcgseed(seed = 4711)
get.lcgseed()
runif.lcg(n, min = 0, max = 1)
rnorm.lcg(n, mean = 0, sd = 1)
rt.lcg(n, df)
}
\arguments{
\item{df}{
number of degrees of freedom, a positive integer, maybe
non-integer.
}
\item{mean, sd}{
means and standard deviation of the normal distributed
innovations.
}
\item{min, max}{
lower and upper limits of the uniform distributed
innovations.
}
\item{seed}{
an integer value, the random number seed.
}
\item{n}{
an integer, the number of random innovations to be
generated.
}
}
\details{
A simple portable random number generator for use in R and
SPlus. We recommend to use this generator only for comparisons
of calculations in R and Splus.
The generator is a linear congruential generator with parameters
\code{LCG(a=13445, c=0, m=2^31-1, X=0)}. It is a simple random
number generator which passes the bitwise randomness test.
}
\value{
A vector of generated random innovations. The value of the
current seed is stored in the variable \code{lcg.seed}.
}
\references{
Altman, N.S. (1988);
\emph{Bitwise Behavior of Random Number Generators},
SIAM J. Sci. Stat. Comput., 9(5), September, 941--949.
}
\examples{
## set.lcgseed -
set.lcgseed(seed = 65890)
## runif.lcg - rnorm.lcg - rt.lcg -
cbind(runif.lcg(10), rnorm.lcg(10), rt.lcg(10, df = 4))
## get.lcgseed -
get.lcgseed()
## Note, to overwrite rnorm, use
# rnorm = rnorm.lcg
# Going back to rnorm
# rm(rnorm)
}
\keyword{programming}