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Random Number Generation
Syntax
.Random.seed <- c(n1,n2,n3)
Description
.Random.seed is an integer vector of length 3, containing
the ``seed'' for all random number generation in R.
The Wichmann-Hill generator is used which has a cycle length of 6.9536e12
(= prod(p-1)/4 where p is the length 3 vector of primes, below),
see p.123 of Applied Statistics (1984) vol.33 which corrects the original
article.
Value
.Random.seed == r[1:3], where r[i] is in 1:p[i],
and p = (30269, 30307, 30323).
References
B.A. Wichmann and I. D. Hill (1982).
Algorithm AS 183: An Efficient and Portable Pseudo-random Number
Generator, Applied Statistics, 31, 188-190; Remarks: 34,p.198
and 35, p.89.
A. De Matteis and S. Pagnutti (1993). Long-range Correlation
Analysis of the Wichmann-Hill Random Number Generator, Statist. Comput.,
3, 67-70.
Note
Initially, there is no seed; a new one is created, using "Randomize".
Hence, student exercises will each have different simulation results, by
default.
See Also
runif, rnorm, ....
Examples
<![CDATA[runif(1); .Random.seed; runif(1); .Random.seed
# If there is no seed, a ``random'' new one is created:
rm(.Random.seed); runif(1); .Random.seed
p.WH <- c(30269, 30307, 30323)
a.WH <- c( 171, 172, 170)
R.seed <- function(i.seed = .Random.seed) (a.WH * i.seed) %% p.WH
my.runif1 <- function(i.seed = .Random.seed)
{ ns <- R.seed(i.seed); sum(ns / p.WH) %% 1 }
##- This shows how 'runif(.)' works, just using R - functions :
rs <- .Random.seed
R.seed(rs); u <- runif(1); .Random.seed; c(u, my.runif1(rs))
]]>