lwMCMC: lightweight Markov Chain Monte Carlo

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from lwMCMC import MCMC

Parameter space sampling with MCMC. See Bayesian inference with the MCMC class below, for an Experimental Geophysics regression.

Posterior distributions	MCMC model fit

• The grid entries reveal the 1-dimensional posterior distributions of our parameters after setting our prior beliefs, as well as the pairwise projections with one and two sigma error contours.

• With the slope parameters's 1.8 +- 0.225 prior, the Bayesian inferred slope is 1.70 +- 0.17.

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Package Layout

• LICENSE - the MIT license, which applies to this package
• README.md - the README file, which you are now reading
• requirements.txt - prerequisites to install this package, used by pip
• setup.py - installer script
• docs/ - contains documentation on package installation and usage
• examples/ - use cases for Bayesian Modeling
• lwMCMC/ - the library code itself
• tests/ - unit tests