Martin Maechler wrote: > OTOH, type=7 is the default, and I guess used in 99.9% of > all uses of quantile, *and* does never use any fuzz ....
Indeed. This also implies that this default should be well-thought when creating a new implementation of the quantile() procedure for a new programming language or library. Most of the time, users use the default procedure, and do not report the procedure used in the statistical analysis reports, scientific or non-scientific articles produced. The differences between all quantiles procedures are minor, unless they are used in crazy scenarios such as a sample size of 2, or with probs=0.001 for a sample of size 1000. But, standardization of procedures is desirable for analysis reproducibility, as well as teaching (see https://doi.org/10.1080/10691898.2006.11910589 ). Hyndman and Fan wanted that software package standardize their definition, but to no avail: See https://robjhyndman.com/hyndsight/sample-quantiles-20-years-later/ In the absence of standard, my personal advice would be to use the same default as a popular statistical software, such as R or SAS. R, Julia and NumPy (python) uses type 7 as default. Microsoft Excel and LibreOffice Calc use type 7 as default (although Excel versions >= 2010 have new procedures). SAS uses type 3 as default, unless prob=0.50 Stata uses type 2 or type 6, depending on the procedure (https://data.princeton.edu/stata/markdown/quantiles.htm) -- Sincerely André GILLIBERT ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
