On Tue, Apr 1, 2014 at 2:08 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 you are not eatimating from a sample, but rather calculating for the > > whole population, you always want ddof=0. > > > > What does Matlab do by default? (Yes, it is a retorical question.) > > R (which is probably a more relevant comparison) does do ddof=1 by default. > > >> I am wondering if there is a good reason to stick to "ddof=0" as the > >> default for "std", or if others would agree with my suggestion to change > >> the default to "ddof=1"? > > > > It is a bad idea to suddenly break everyone's code. > > It would be a disruptive transition, but OTOH having inconsistencies > like this guarantees the ongoing creation of new broken code. > > This topic comes up regularly. The original choice was made for numpy 1.0b1 by Travis, see this later thread.<http://thread.gmane.org/gmane.comp.python.numeric.general/25720/focus=25721>At this point it is probably best to leave it alone. Chuck
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