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From Vladimir Sitnikov <sitnikov.vladi...@gmail.com>
Subject Re: [GitHub] jmeter issue #296: Bug 61078 - Percentile calculation error
Date Tue, 09 May 2017 10:08:18 GMT
Felix>I wonder if we should change our implementation at all.

So do I.
I wish JMeter would just throw an error when user tries to calculate 90%
percentile out of 5 values =)

Felix>Note I share your thoughts on using a dedicated library but
Felix> commons-math may be overkill in terms of performance compared to
Felix> HdrHistogram

I agree HdrHistogram might be the only way to compute high percentiles with
sane amount of memory.

Felix>R and numpy will interpolate the median and the percentiles/quantiles.

Technically speaking, R has 9 types of quantile calculation:
https://stat.ethz.ch/R-manual/R-devel/library/stats/html/quantile.html

There's a comment:

R.quantile.doc>Further details are provided in Hyndman and Fan (1996) who
recommended type 8. The default method is type 7, as used by S and by R <
2.0.0.

As far as I understand that, "type 8" is somewhat better, however R
defaults to type 7 for backward compatibility reasons.

Here's what R version 3.4.0 (2017-04-21) produces:

quantile(c(15, 20, 35, 40, 50), c(0.05, 0.3, 0.4, 0.5, 1.0))
  5%  30%  40%  50% 100%
  16   23   29   35   50

quantile(c(15, 20, 35, 40, 50), c(0.05, 0.3, 0.4, 0.5, 1.0), type=8)
      5%      30%      40%      50%     100%
15.00000 19.66667 27.00000 35.00000 50.00000


Vladimir

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