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[ascl:2001.015] gnm: The MCMC Jagger

gnm is an implementation of the affine-invariant sampler for Markov chain Monte Carlo (MCMC) that uses the Gauss-Newton-Metropolis (GNM) Algorithm. The GNM algorithm is specialized in sampling highly non-linear posterior probability distribution functions of the form exp(-||f(x)||^2/2). The code includes dynamic hyper-parameter optimization to increase performance of the sampling; other features include the Jacobian tester and an error bars creator.

Code site:
http://montecarlosampler.com/ https://github.com/mugurbil/gnm
Described in:
https://ui.adsabs.harvard.edu/abs/2020arXiv200103530U
Bibcode:
2020ascl.soft01015U

Views: 677

ascl:2001.015
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