Commit ad316e65 authored by Xisco Jimenez Forteza's avatar Xisco Jimenez Forteza
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Domain dedicated to the Ringdown stacking project. All code, files and plots should be reasonably documented in the README file.
RDown.m: RDown package file that loads the functions needed for our computation.
RDown.nd: RDown mathematica file to add/modify our RDown functions. Every time you modify and save this file, the RDown.m package is automatically updated.
RDanalysis.nb: Mathematica notebook used to generate our results.
mcmc.m: Mathematica package to run mcmc samplers.
l2: Folder containing the modes and tones data. It is taken from Berti & Cardoso.
Mathematica Markov Chain Monte Carlo
====================================
Mathematica package containing a general-purpose [Markov chain Monte Carlo](http://en.wikipedia.org/wiki/Markov_chain_Monte_Carlo) routine I wrote. Includes various examples and documentation.
### Features:
* Convenience wrapper for fitting models to arbitrary-dimensional data with Gaussian errors
* Handles both real-valued and discrete-valued model parameters
* Uses Metropolis algorithm with decaying exponential proposal distribution
* Progress monitor; support for auto save/resume
### Files:
* `mcmc.m`: Package file
* `mcmc_demonst.nb`: Demonstrations and documentation
For a good Python MCMC implementation, check out [emcee](http://dan.iel.fm/emcee).
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