[SciPy-User] Python significance / error interval / confidence interval module?

[Bruce Southey]

On 06/17/2011 11:21 AM, josef.pktd at gmail.com wrote:
> On Fri, Jun 17, 2011 at 11:12 AM, Gael Varoquaux
> <gael.varoquaux at normalesup.org>  wrote:
>> On Fri, Jun 17, 2011 at 05:08:16PM +0200, Christoph Deil wrote:
>>>     I am looking for a python module for significance / error interval /
>>>     confidence interval computation.
>> How about http://pypi.python.org/pypi/uncertainties/
>>
>>>     Specifically I am looking for Poisson rate estimates in the presence of
>>>     uncertain background and / or efficiency, e.g. for an "on/off
>>>     measurement".
>> Wow, that seems a bit more involved than Gaussian error statistics. I am
>> not sure that the above package will solve your problem.
>>
>>>     The standard method of Rolke I am mainly interested in is available in
>>>     ROOT and RooStats, a C++ high energy physics data analysis package:
>> If you really need proper Poisson-rate errors, then you might indeed not
>> to translate the Rolke method to Python. How about contributing it to
>> uncertainties.
> It's a very specific model, and I doubt it's covered by any general
> packages, but implementing
> http://lanl.arxiv.org/abs/physics/0403059
> assuming this is the background for it, doesn't sound too difficult.
>
> The main work it looks like is keeping track of all the different
> models and parameterizations.
> scipy.stats.distributions and scipy.optimize (fmin, fsolve) will cover
> much of the calculations.
>
> (But then of course there is testing and taking care of corner cases
> which takes at least several times as long as the initial
> implementation, in my experience.)
>
> Josef
>
>> G
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Actually I am more interested in how this differs from a generalized 
linear model where modeling Poisson or negative binomial distribution is 
feasible.

Bruce