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[ascl:1706.005] LMC: Logarithmantic Monte Carlo

LMC is a Markov Chain Monte Carlo engine in Python that implements adaptive Metropolis-Hastings and slice sampling, as well as the affine-invariant method of Goodman & Weare, in a flexible framework. It can be used for simple problems, but the main use case is problems where expensive likelihood evaluations are provided by less flexible third-party software, which benefit from parallelization across many nodes at the sampling level. The parallel/adaptive methods use communication through MPI, or alternatively by writing/reading files, and mostly follow the approaches pioneered by CosmoMC (ascl:1106.025).

Code site:
https://github.com/abmantz/lmc https://pypi.python.org/pypi/lmc
Appears in:
http://adsabs.harvard.edu/abs/2017MNRAS.469.1476S
Bibcode:
2017ascl.soft06005M

ascl:1706.005
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