mohanagr / PyMC

Monte Carlo Markov Chain sampler for a given function

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PyMC

Monte Carlo Markov Chain sampler for a given function

Edit testfunc.py to implement your own model.

Purpose

To generate most likely values for cosmological parameters by running MCMC with physical model and Planck data.

Current physical model calculates the theoretical peak spacing of the CMB angular Power Spectrum using theory in Hu, Sugiyama 1994 and M. Doran, M.Lilley et. al. 2001 and fitting formulas given in M. Doran and M. Lilley, 2002. This is comapred with the peak spacing data in Planck satellite 2015 release.

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Monte Carlo Markov Chain sampler for a given function

License:MIT License


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Language:Python 100.0%