Set Seed for Random Number Generators
DESCRIPTION:
Puts the random number generator in a reproducible state.
USAGE: 
set.seed(i)
REQUIRED ARGUMENTS:
i:
be an integer between 0 and 1000.
SIDE EFFECTS:
Sets the value of the .Random.seed object in the working directory.
DETAILS:
Random number generators in S-PLUS are all based upon a single uniform random number generator that generates numbers in a very long, but ultimately periodic sequence. The position in the sequence is held in object .Random.seed. Function set.seed sets .Random.seed so that subsequent calls to random number generator functions (runif, rnorm, etc.) will generate numbers from a new portion of the overall cycle.

Random number generation in S-PLUS is adapted from Marsaglia (1973); see Kennedy and Gentle (1980) for background information.

REFERENCES:
Kennedy, W. J. and Gentle, J. E. (1980). Statistical Computing. Marcel Dekker, New York.

Marsaglia, G. et al. (1973). Random Number Package: "Super-Duper". School of Computer Science, McGill University.

SEE ALSO:
in Appendix 2 of Becker, Chambers and Wilks, or on-line.

rbeta, rcauchy, rchisq, rexp, rf, rgamma, rlogis, rlnorm, rnorm, rstab, rt, runif, rbinom, rgeom, rhyper, rpois, rwilcox, sample.

EXAMPLES: 
# to reproduce random samples:
set.seed(153)
   # do some work
set.seed(153)
   # the same "random" numbers occur.
# the same effect can be created by saving .Random.seed and then
# assigning that value to .Random.seed later.