Re: [Rd] Randomness not due to seed

From: Paul Gilbert <>
Date: Wed, 20 Jul 2011 14:42:07 +0000

It does not look like your calculation is using the random number generator, so the other responses are probably more to the point.

However, beware that setting the seed is not enough to guarantee the same random numbers. You need to also make sure you are using the same uniform RNG and any other generators you use, such as the normal generator. R has a large selection of possibilities. Your start up settings could change the default behaviour. Also, relying on the default will be a bit risky if you are interested in reproducible calculations, because the R default could change in the future (as it has in the past, and as has the Splus generator in the past).

If the RNG is important for your reproducible calculations then you might want to look at the examples and tests in the setRNG package.


> -----Original Message-----
> From: [mailto:r-devel-bounces_at_r-
>] On Behalf Of jeroen00ms
> Sent: July 19, 2011 9:13 AM
> To:
> Subject: [Rd] Randomness not due to seed
> I am working on a reproducible computing platform for which I would
> like to
> be able to _exactly_ reproduce an R object. However, I am experiencing
> unexpected randomness in some calculations. I have a hard time finding
> out
> exactly how it occurs. The code below illustrates the issue.
> mylm1 <- lm(dist~speed, data=cars);
> mylm2 <- lm(dist~speed, data=cars);
> identical(mylm1, mylm2); #TRUE
> makelm <- function(){
> return(lm(dist~speed, data=cars));
> }
> mylm1 <- makelm();
> mylm2 <- makelm();
> identical(mylm1, mylm2); #FALSE
> When inspecting both objects there seem to be some rounding
> differences.
> Setting a seed does not make a difference. Is there any way I can
> remove
> this randomness and exactly reproduce the object every time?
> --
> View this message in context:
> not-due-to-seed-tp3678082p3678082.html
> Sent from the R devel mailing list archive at
> ______________________________________________
> mailing list

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