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From "OlgaK (JIRA)" <j...@apache.org>
Subject [jira] [Issue Comment Deleted] (RNG-37) Ziggurat algorithm
Date Mon, 18 Dec 2017 02:31:00 GMT

     [ https://issues.apache.org/jira/browse/RNG-37?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

OlgaK updated RNG-37:
---------------------
    Comment: was deleted

(was: {quote}Then it looks like the whole procedure needs to be adapted, not only the tail.
Indeed generating a single 32-bits value (nextInt(), at line 98) won't return any of the double
values (64-bits) that would require a different setting of any one of the missing 32-bits.{quote}
I think missing 32-bits contribute to the precision (having 7 decimal digits vs having 16).
For Gaussian in high density area having 8th and after digits doesn't make a notable effect,
while in the low density are it does indeed. 
I'm fairly sure it's just the tail. Besides when one tries to increase precision switching
from float to double but still keeps the same number of fitting blocks... 
Overall the fit is so to say good enough to pass the test. But it's not a big deal to switch
to Long. Moreover, it has been my original thought to make the calcs in long and I've even
added the missing long random in the main codebase but then I switched to int. 
Actually as you may notice in the paper there is another application of the algorithm - to
fit exponential distribution. I've tried to add this one as well but there was severe test
failure and since it has not been requested, I decided to skip it. But there indeed all numbers
need to be recalculated.  
{quote}Then, I wonder how to make sure that no holes remain. Is it possible to set up a unit
test? If not, a last resort idea might be to make a plot of many generated values, superimposed
with a plot of a uniform sampling, and look for anomalies (empty regions). {quote} The rng
has a very well done testing module. It allows people, coming from street or bb, to test their
code adding just a single line in the test suite. I was really impressed. I didn't get into
details by what criteria it assesses the quality of generated distribution but it definitely
more than just a single number pick (based on what I recall how the 2d distribution test failed).
If you think it doesn't make a check for the wholes, it definitely would be a great idea to
add it (not just for Ziggurat test but for all distributions). The person who had written
the testing module, definitely could do it better and faster. For a "side person" imho it'd
require substantial time and efforts. One can make it as a task for "Help wanted" bb but don't
have over expectations :). 
I'll do switch int -> long. Try to do it to the nearest weekend.    

I didn't get your last message    "Fix Version/s" ??         )

> Ziggurat algorithm
> ------------------
>
>                 Key: RNG-37
>                 URL: https://issues.apache.org/jira/browse/RNG-37
>             Project: Commons RNG
>          Issue Type: Wish
>            Reporter: Gilles
>            Priority: Minor
>             Fix For: 1.1
>
>         Attachments: ziggurat.buggy.png
>
>
> Fast algorithm for sampling a Gaussian distribution: https://en.wikipedia.org/wiki/Ziggurat_algorithm



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