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r get seed

a single value, interpreted as an integer, or NULL (see ‘Details’).
Wichmann, B. A. and Hill, I. D. (1982). Algorithm AS 183: An Efficient and Portable Pseudo-random Number Generator. Applied Statistics, 31, 188–190; Remarks: 34, 198 and 35, 89. doi: 10.2307/2347988.
Reeds, J., Hubert, S. and Abrahams, M. (1982–4). C implementation of SuperDuper, University of California at Berkeley. (Personal communication from Jim Reeds to Ross Ihaka.)
Marsaglia, G. (1997). A random number generator for C. Discussion paper, posting on Usenet newsgroup sci.stat.math on September 29, 1997.
RNGversion can be used to set the random generators as they were in an earlier R version (for reproducibility).
The two seeds are the Tausworthe and congruence long integers, respectively. A one-to-one mapping to S’s .Random.seed[1:12] is possible but we will not publish one, not least as this generator is not exactly the same as that in recent versions of S-PLUS.
Marsaglia, G. and Zaman, A. (1994). Some portable very-long-period random number generators. Computers in Physics, 8, 117–121. doi: 10.1063/1.168514.
A ‘combined multiple-recursive generator’ from L’Ecuyer (1999), each element of which is a feedback multiplicative generator with three integer elements: thus the seed is a (signed) integer vector of length 6. The period is around 2^191.
RNGversion returns the same information as RNGkind about the defaults in a specific R version.
R get seed .Random.seed is an integer vector, containing the random number generator (RNG) state for random number generation in R . It can be saved and restored, but should not be altered by