gnm: The MCMC Jagger

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Ada Coda
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gnm: The MCMC Jagger

Post by Ada Coda » Sat Feb 01, 2020 4:41 am

gnm: The MCMC Jagger

Abstract: 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.

Credit: Ugurbil, Mehmet

Site: https://github.com/mugurbil/gnm
https://ui.adsabs.harvard.edu/abs/2020a ... U/abstract

Bibcode: 2020ascl.soft01015U

ID: ascl:2001.015

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