RGW: Goodman-Weare Affine-Invariant Sampling

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Ada Coda
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RGW: Goodman-Weare Affine-Invariant Sampling

Post by Ada Coda » Wed Nov 29, 2017 7:02 pm

RGW: Goodman-Weare Affine-Invariant Sampling

Abstract: RGW is a lightweight R-language implementation of the affine-invariant Markov Chain Monte Carlo sampling method of Goodman & Weare (2010). The implementation is based on the description of the python package emcee (ascl:1303.002).

Credit: Mantz, Adam B.

Site: https://cran.r-project.org/web/packages/rgw/index.html
http://adsabs.harvard.edu/abs/2017MNRAS.472.2877M

Bibcode: 2017ascl.soft11006M

ID: ascl:1711.006
Last edited by Ada Coda on Sun Jun 10, 2018 8:03 pm, edited 1 time in total.
Reason: Updated code entry.

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