R devel - Sep 2018 - Bias in R's random integers?

> From: Duncan Murdoch <murdoch.duncan at gmail.com>
> Let's try it:
> 
>  > m <- (2/5)*2^32
>  > m > 2^31
> [1] FALSE
>  > x <- sample(m, 1000000, replace = TRUE)
>  > table(x %% 2)
> 
>       0      1
> 399850 600150
> 
> Since m is an even number, the true proportions of evens and odds should 
> be exactly 0.5.  That's some pretty strong evidence of the bug in the 
> generator. 

It seems to be a recently-introduced bug.  Here's output with R-2.15.1:

  R version 2.15.1 (2012-06-22) -- "Roasted Marshmallows"
  Copyright (C) 2012 The R Foundation for Statistical Computing
  ISBN 3-900051-07-0
  Platform: x86_64-unknown-linux-gnu (64-bit)
  
  R is free software and comes with ABSOLUTELY NO WARRANTY.
  You are welcome to redistribute it under certain conditions.
  Type 'license()' or 'licence()' for distribution details.
  
  R is a collaborative project with many contributors.
  Type 'contributors()' for more information and
  'citation()' on how to cite R or R packages in publications.
  
  Type 'demo()' for some demos, 'help()' for on-line help, or
  'help.start()' for an HTML browser interface to help.
  Type 'q()' to quit R.
  
  > set.seed(123)
  > m <- (2/5)*2^32
  > m > 2^31
  [1] FALSE
  > x <- sample(m, 1000000, replace = TRUE)
  > table(x %% 2)
  
       0      1 
  499412 500588 
  
So I doubt that this has anything to do with bias from using 32-bit
random values.

   Radford Neal

On 20/09/2018 11:01 AM, Radford Neal wrote:
>> From: Duncan Murdoch <murdoch.duncan at gmail.com>
> 
>> Let's try it:
>>
>>   > m <- (2/5)*2^32
>>   > m > 2^31
>> [1] FALSE
>>   > x <- sample(m, 1000000, replace = TRUE)
>>   > table(x %% 2)
>>
>>        0      1
>> 399850 600150
>>
>> Since m is an even number, the true proportions of evens and odds
should
>> be exactly 0.5.  That's some pretty strong evidence of the bug in
the
>> generator.
> 
> 
> It seems to be a recently-introduced bug.  Here's output with R-2.15.1:
> 
>    R version 2.15.1 (2012-06-22) -- "Roasted Marshmallows"
>    Copyright (C) 2012 The R Foundation for Statistical Computing
>    ISBN 3-900051-07-0
>    Platform: x86_64-unknown-linux-gnu (64-bit)
>    
>    R is free software and comes with ABSOLUTELY NO WARRANTY.
>    You are welcome to redistribute it under certain conditions.
>    Type 'license()' or 'licence()' for distribution
details.
>    
>    R is a collaborative project with many contributors.
>    Type 'contributors()' for more information and
>    'citation()' on how to cite R or R packages in publications.
>    
>    Type 'demo()' for some demos, 'help()' for on-line help,
or
>    'help.start()' for an HTML browser interface to help.
>    Type 'q()' to quit R.
>    
>    > set.seed(123)
>    > m <- (2/5)*2^32
>    > m > 2^31
>    [1] FALSE
>    > x <- sample(m, 1000000, replace = TRUE)
>    > table(x %% 2)
>    
>         0      1
>    499412 500588
>    
> So I doubt that this has anything to do with bias from using 32-bit
> random values.
There are two bugs, one recent one (allowing fractional m to slip 
through) and one old one (the bias).  The test above shows the bias with 
m+1, i.e. in R 2.15.1

 > x <- sample(m + 1, 1000000, replace = TRUE)
 > table(x %% 2)

      0      1
466739 533261


and you can see it in the original m with

   x <- sample(m, 1000000, replace = TRUE)
   plot(density(x[x %% 2 == 0]))

Duncan Murdoch