On Mi, 2014-03-05 at 10:21 -0800, David Goldsmith wrote:
Date: Wed, 05 Mar 2014 17:45:47 +0100 From: Sebastian Berg <sebastian@sipsolutions.net> Subject: [Numpy-discussion] Adding weights to cov and corrcoef To: numpy-discussion@scipy.org 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...
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