I am trying to understand how set.seed works in R. I understand it, can reproduce random samples, but I don't know what is the difference between set.seed(1) and set.seed(123) ?
What do the argument in the bracket mean ?
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sgibb
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mynameisJEFF
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2 Answers
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The seed argument in set.seed is a single value, interpreted as an integer (as defined in help(set.seed()). The seed in set.seed produces random values which are unique to that seed (and will be same irrespective of the computer you run and hence ensures reproducibility). So the random values generated by set.seed(1) and set.seed(123) will not be the same but the random values generated by R in your computer using set.seed(1) and by R in my computer using the same seed are the same.
set.seed(1)
x<-rnorm(10,2,1)
> x
[1] 1.373546 2.183643 1.164371 3.595281 2.329508 1.179532 2.487429 2.738325 2.575781 1.694612
set.seed(123)
y<-rnorm(10,2,1)
> y
[1] 1.4395244 1.7698225 3.5587083 2.0705084 2.1292877 3.7150650 2.4609162 0.7349388 1.3131471 1.5543380
> identical(x,y)
[1] FALSE
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First of all, thanks a lot for explaining it in a simple way. But, how do I know what number must go in as a parameter? – Ankur Sinha Jun 22 '14 at 07:22
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It doesn't matter which number you choose since they all generate random values. – Metrics Jun 22 '14 at 13:34
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The majority of computer programs uses deterministic algorithms to generate random numbers (which is the reason why the numbers they generate are not truly random, but pseudorandom, which is good enough for most purposes). R is no different, and you can think of the random numbers it generates as being part of a very long string of seemingly-random numbers that, when summoned, just starts at some point and spits out a sequence of numbers for you.
By using set.seed(), you are basically giving the program a starting point instead of letting it choose its own. That's why any user running the same seed number will get the same results.
You can run ?RNGkind for more information on the subject.
Waldir Leoncio
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Apparently, there's an R package called `random` that generates true random variables. Haven't tested it though (as I said, pseudorandom is usually good enough): http://dirk.eddelbuettel.com/code/random.html – Waldir Leoncio Aug 13 '13 at 18:06