[Rd] Randomness not due to seed

[William Dunlap]

Did you actually see some rounding differences?

The lm objects made in the calls to maklm will
differ in the environments attached to the formula
(because you made the formula in the function).  If
I change both copies of that .Environment attribute
to .GlobalEnv (or any other environment), then identical
reports the objects are the same:

  > attr(attr(mylm1$model, "terms"), ".Environment") <- .GlobalEnv
  > attr(mylm1$terms, ".Environment") <- .GlobalEnv
  > attr(attr(mylm2$model, "terms"), ".Environment") <- .GlobalEnv
  > attr(mylm2$terms, ".Environment") <- .GlobalEnv
  > identical(mylm1, mylm2)
  [1] TRUE 

Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com 

> -----Original Message-----
> From: r-devel-bounces at r-project.org [mailto:r-devel-bounces at r-project.org] On Behalf Of jeroen00ms
> Sent: Tuesday, July 19, 2011 6:13 AM
> To: r-devel at r-project.org
> 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: http://r.789695.n4.nabble.com/Randomness-not-due-to-seed-
> tp3678082p3678082.html
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> 
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