On Thu, Mar 6, 2014 at 1:40 PM, Sebastian Berg <[email protected]>wrote:
> On Mi, 2014-03-05 at 10:21 -0800, David Goldsmith wrote: > > > > > > > > Date: Wed, 05 Mar 2014 17:45:47 +0100 > > From: Sebastian Berg <[email protected]> > > Subject: [Numpy-discussion] Adding weights to cov and corrcoef > > To: [email protected] > > Message-ID: <1394037947.21356.20.camel@sebastian-t440> > > Content-Type: text/plain; charset="UTF-8" > > > > Hi all, > > > > in Pull Request https://github.com/numpy/numpy/pull/3864 Neol > > Dawe > > suggested adding new parameters to our `cov` and `corrcoef` > > functions to > > implement weights, which already exists for `average` (the PR > > still > > needs to be adapted). > > > > > > Do you mean adopted? > > > > What I meant was that the suggestion isn't actually implemented in the > PR at this time. So you can't pull it in to try things out. > > > > > However, we may have missed something obvious, or maybe it is > > already > > getting too statistical for NumPy, or the keyword argument > > might be > > better `uncertainties` and `frequencies`. So comments and > > insights are > > very welcome :). > > > > > > +1 for it being "too baroque" for NumPy--should go in SciPy (if it > > isn't already there): IMHO, NumPy should be kept as "lean and mean" as > > possible, embellishments are what SciPy is for. (Again, IMO.) > > > > Well, on the other hand, scipy does not actually have a `std` function > of its own, I think. So if it is quite useful I think this may be an > option (I don't think I ever used weights with std, so I can't argue > strongly for inclusion myself). Unless adding new functions to > `scipy.stats` (or just statsmodels) which implement different types of > weights is the longer term plan, then things might bite... > AFAIK there's currently no such plan. Ralf
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