Am 09.05.2017 09:11, schrieb pmouawad:
Github user pmouawad commented on the issue:
https://github.com/apache/jmeter/pull/296
Hello @abalanonline ,
Thanks for your replies and explanations !
I am not a math expert as you seem to be, so I have few questions
you may be able to help on:
1. Thanks to your comment, I see default method is LEGACY, and the
one you have created is R_1. Do you have some insights on the
different method and their limits / use cases ?
2. Why does the "bug" you report affect all libraries I checked
(HdrHistogram, https://github.com/tdunning/t-digest/ and JOrphan ) ?
Can't it be due to a different method estimation algorithm ?
Note I share your thoughts on using a dedicated library but
commons-math may be overkill in terms of performance compared to
HdrHistogram or t-digest.
I have tried to do a bit of research on percentiles, quantiles and
median.
It looks to me, that those "points" are more like ranges, and there is
no exact value.
R and numpy will interpolate the median and the percentiles/quantiles.
The statistics module
of python 3 has three different median implementations called median,
median_high and median_low,
that interpolate, give the highest possible median and the lowest.
Wikipedia (the german one), gives a definition of an "Empirisches
Quantile" (empiric quantile),
where it settles on the lower border of the quantiles (and therefore the
median).
I wonder if we should change our implementation at all.
Felix
Thanks
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