Hi, I don't have time to read the posted links yet
But I am OK to have the same way to calculate percentiles and documented it Antonio 2017-05-28 11:51 GMT+02:00 Philippe Mouawad <philippe.moua...@gmail.com>: > Hello, > After reading further on this topic and also reading the different > comments, my position would be: > - switch everywhere to R1 (also in commons-math) > - use the PR from contributor for the median and jorphan computations > - document the change and algo somewhere > > From my understanding, tests having large results should not be affected by > change. > > This would at least make computations uniform until we decide what library > to use. > > I need your go before going further. > > If we decide for statusquo then please comment on respective bugs to > explain to reported and contributor why we won't change anything. > > Regards > > On Tuesday, May 9, 2017, Felix Schumacher <felix.schumacher@ > internetallee.de> > wrote: > > > 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 > >> > >> > >> --- > >> If your project is set up for it, you can reply to this email and have > >> your > >> reply appear on GitHub as well. If your project does not have this > feature > >> enabled and wishes so, or if the feature is enabled but not working, > >> please > >> contact infrastructure at infrastruct...@apache.org or file a JIRA > ticket > >> with INFRA. > >> --- > >> > > > > -- > Cordialement. > Philippe Mouawad. >
