[OpenSTA-devel] [ opensta-Bugs-1406888 ] Distribution of RANDOM variable sequences is non-uniform

[SourceForge.net <no...@so...>]

Bugs item #1406888, was opened at 2006-01-15 17:31
Message generated for change (Comment added) made by velivis
You can respond by visiting: 
https://sourceforge.net/tracker/?func=detail&atid=110857&aid=1406888&group_id=10857

Please note that this message will contain a full copy of the comment thread,
including the initial issue submission, for this request,
not just the latest update.
Category: Script Language
Group: Behavioral
>Status: Closed
Resolution: Accepted
Priority: 5
Private: No
Submitted By: Daniel Sutcliffe (dansut)
Assigned to: Daniel Sutcliffe (dansut)
Summary: Distribution of RANDOM variable sequences is non-uniform

Initial Comment:
Given a RANDOM variable you would expect that for every
call to GENERATE there was an equal chance of getting
any of the potential results - this appears to not be
the case and for any set of potential results there
will be certain result values which have a higher
chance of being returned and others which have a lower
chance.

As an example given potential results of 1 and 2, there
is roughly 53% chance of getting a 2 and 47% chance of
getting a 1.  This type/scale of result weighting
applies to all result set sizes - giving a random
result that although "fairly random" could potentially
throw out test results in certain very specific
circumstances.

This problem is present on all platforms for the
OpenSTA 1.4.3 release and earlier.

----------------------------------------------------------------------

>Comment By: Bernie Velivis (velivis)
Date: 2007-10-18 08:40

Message:
Logged In: YES 
user_id=1868094
Originator: NO

Dan wrote: "Given a RANDOM variable you would expect that for every call
to GENERATE there was an equal chance of getting any of the potential
results". 

This is not true. True random number generators will generate duplicates
quite often. However this does tend to even out over time (larger ranges
and more samples both lead to more uniform distributions).

The randomness of a set of numbers can be quantified by calculating the
standard deviation. I generated 100 random numbers in SCL and using the
Excel STDEVA function calculated a standard deviation of 28. I also created
a list of 100 numbers using the excel rand() function and for it I
calculated a standard deviation of 31 (slightly more random). Both lists
contained many duplicates. 

If you want to generate a list of pseudo random numbers with no repeating
values, generate it outside of SCL, randomize its order, and import the
numbers into a list of integers and use the NEXT command to access them
sequentially

----------------------------------------------------------------------

You can respond by visiting: 
https://sourceforge.net/tracker/?func=detail&atid=110857&aid=1406888&group_id=10857