[AstroPy] [ANN] Nestle: Nested sampling

[Kyle Barbary]

Yes, possibly! Nestle currently implements the basic MultiNest method, but
doesn't implement later improvements such as importance reweighting or
polychord. I'm open to contributions and improvements. (But be mindful of
reading the MultiNest source code due to licensing issues!)

Best,
-- Kyle

On Tue, Sep 29, 2015 at 1:03 PM, Johann Cohen-Tanugi <
johann.cohentanugi at gmail.com> wrote:

> likewise!
> Any prospect toward the polychord extension? See
> http://arxiv.org/abs/1506.00171v1
> cheers,
> Johann
>
>
> On 09/29/2015 10:30 AM, Wolfgang Kerzendorf wrote:
>
> HI Kyle,
>
> Very nice. I'll definitely have a look at that.
>
> Cheers,
>    Wolfgang
> --
> Dr. Wolfgang E Kerzendorf
> ESO Fellow
> European Southern Observatory
> Karl-Schwarzschild Str. 2, 85748
> Garching bei Muenchen, Germany
>
> On Tue, Sep 29, 2015 at 6:09 AM Kyle Barbary < <kylebarbary at gmail.com>
> kylebarbary at gmail.com> wrote:
>
>> Hi all,
>>
>> I'm pleased to announce the initial release of Nestle, a small Python
>> package for nested sampling. ("Nestle" rhymes with "wrestle".) Nested
>> sampling is a statistical technique for parameter estimation and model
>> comparison, commonly used in cosmology. We've been using it in the sncosmo
>> package and have found it to be a robust global optimizer in addition to
>> its more typically cited benefits.
>>
>> Nestle implements an algorithm similar to that used in the MultiNest
>> software, but in an open-source (MIT) licensed and easy-to-install (pure
>> Python) package. (It was written based only on the literature, not the
>> MultiNest source code.) In addition to this algorithm, Nestle also
>> implements the "classic" nested sampling algorithm and the "single
>> ellipsoid" algorithm.
>>
>> Nestle depends on only numpy and (optionally) scipy and supports both
>> Python 3 and Legacy Python (formerly known as Python 2).
>>
>> docs:  <http://kbarbary.github.io/nestle>http://kbarbary.github.io/nestle
>> source:  <http://github.com/kbarbary/nestle>
>> http://github.com/kbarbary/nestle
>>
>> I'd appreciate any feedback on this initial release, particularly about
>> application to real-world problems and comparisons with results from
>> MultiNest. Thanks!
>>
>> - Kyle
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>>
>
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