Hello All, We are working to add support for the Tukey-Kramer statistical test, and it relies upon an involved computation of the critical values of the Studentized Range, for which a Fortran routine has been published. Using this Fortran would be much quicker in terms of development and likely quicker in computation than our best Python implementation. The code is published in a journal article, but I'm not sure if that means that the code is publicly available, or what license or copyright might be retained. I have contacted one of the original authors to ask him about it and am awaiting a response. The paper the code is in is available from JSTOR, and the raw code is available in various places <http://ftp.uni-bayreuth.de/math/statlib/apstat/190> on the internet both in original form and sometimes with improvements. Algorithm AS 190: Probabilities and Upper Quantiles for the Studentized Range <https://www.jstor.org/stable/2347300?seq=1> R. E. Lund and J. R. Lund Journal of the Royal Statistical Society. Series C (Applied Statistics) Vol. 32, No. 2 (1983), pp. 204-210 (7 pages) Published By: Wiley DOI: 10.2307/2347300 In SciPy there is already use of several algorithms also published by Journal of the Royal Statistical Society (these can also be found on JSTOR). In git history I see they were added some 18 years ago: PRHO: Algorithm AS 89 Appl. Statist. (1975) Vol.24, No. 3, P377 in scipy/stats/statlib/spearman.f POLY: ALGORITHM AS 181.2 APPL. STATIST. (1982) VOL. 31, NO. 2 in scipy/stats/statlib/swilk.f I’ve investigated online for other licensed use of these algorithms, but I have not seen anything concrete. I closest use I was able to find is a direct translation of the algorithm <https://foundry.sandia.gov/releases/latest/javadoc-api/gov/sandia/cognition/statistics/distribution/StudentizedRangeDistribution.APStat.html> we are interested in, AS 190, to Java by Sandia National Laboratories, which "is released under the open source BSD License.” <https://foundry.sandia.gov/> Does anyone have experience with this source or insight into whether the inclusion of this Fortran in SciPy is fair game? Cheers, Sam Wallan