daniel-furman / lwmcmc Goto Github PK

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.

• 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