On Tue, Apr 1, 2014 at 5:11 PM, Nathaniel Smith <n...@pobox.com> wrote: > On Tue, Apr 1, 2014 at 9:51 PM, Ralf Gommers <ralf.gomm...@gmail.com> wrote: >> >> >> >> On Tue, Apr 1, 2014 at 10:08 PM, Nathaniel Smith <n...@pobox.com> wrote: >>> >>> On Tue, Apr 1, 2014 at 9:02 PM, Sturla Molden <sturla.mol...@gmail.com> >>> wrote: >>> > Haslwanter Thomas <thomas.haslwan...@fh-linz.at> wrote: >>> > >>> >> Personally I cannot think of many applications where it would be >>> >> desired >>> >> to calculate the standard deviation with ddof=0. In addition, I feel >>> >> that >>> >> there should be consistency between standard modules such as numpy, >>> >> scipy, and pandas. >>> > >>> > ddof=0 is the maxiumum likelihood estimate. It is also needed in >>> > Bayesian >>> > estimation. >>> >>> It's true, but the counter-arguments are also strong. And regardless >>> of whether ddof=1 or ddof=0 is better, surely the same one is better >>> for both numpy and scipy. >> >> If we could still choose here without any costs, obviously that's true. This >> particular ship sailed a long time ago though. By the way, there isn't even >> a `scipy.stats.std`, so we're comparing with differently named functions >> (nanstd for example). > > Presumably nanstd is a lot less heavily used than std, and presumably > people expect 'nanstd' to be a 'nan' version of 'std' -- what do you > think of changing nanstd to ddof=0 to match numpy? (With appropriate > FutureWarning transition, etc.)
numpy is numpy, a numerical library scipy.stats is stats and behaves differently. (axis=0) nanstd in scipy.stats will hopefully also go away soon, so I don't think it's worth changing there either. pandas came later and thought ddof=1 is worth more than consistency. I don't think ddof defaults's are worth jumping through deprecation hoops. (bias in cov, corrcoef is "non-standard" ddof) Josef > > -- > Nathaniel J. Smith > Postdoctoral researcher - Informatics - University of Edinburgh > http://vorpus.org > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
