R: bizarre behavior of set.seed()

Question

Odd thing happens when in R when I do set.seed(0) and set.seed(1);

set.seed(0)
sample(1:100,size=10,replace=TRUE)
#### [1] 90 27 38 58 91 21 90 95 67 63


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Answer 1

As you can see from the other answer, seeds 0 and 1 result in almost similar initial states. In addition, Mersenne Twister PRNG has a severe limitation - "almost similar initial states will take a long time to diverge"

It is therefore advisable to use alternatives like WELL PRNG (which can be found in randtoolbox package)