[SciPy-dev] stats.models report/preannouncement
Wed Aug 19 20:10:05 CDT 2009
On Wed, Aug 19, 2009 at 9:07 PM, Robert Kern<email@example.com> wrote:
> On Wed, Aug 19, 2009 at 18:05, <firstname.lastname@example.org> wrote:
>> 2009/8/19 Stéfan van der Walt <email@example.com>:
>>> Hi guys,
>>> 2009/8/19 firstname.lastname@example.org <email@example.com>:
>>>> Most importantly, almost every result has been verified with at least
>>>> one other statistical package, R, Stata and SAS. The guiding principal
>>>> for the rewrite was that all numbers have to be verified, even if we
>>>> don't manage to cover everything. There are a few remaining issues,
>>>> that we hope to clear up by next week. Not all parts of the code have
>>>> been tested for unexpected inputs. We are currently adding checks for,
>>>> and conversions of array types and dimension. Additionally, many of
>>>> the tests call rpy to compare the results directly with R. We use an
>>>> extended wrapper for R models in the test suite. This provides greater
>>>> flexibility writing new test cases, but will eventually be replaced by
>>>> hard coded expected results.
>>>> The code is written for plain NumPy arrays.
>>> Thanks for all your hard work!
>>>> We can either package it as a scikit or as a independent
>>>> package distributed through pypi.
>>> SciKits are also distributed through pypi. It's basically just a
>>> naming/namespace convention. All scikits.* packages from pypi are
>>> also listed automatically on
>> Is it worth setting up a scikits if the code goes into scipy in a few months?
>> I never looked at how high the setup costs for a scikits are. A plain
>> python package looks easier. However, I have no experience in
>> distributing a package.
> It's always a chunk of work. It's no worse with scikits.
Is it any better? ;)
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