AffineInvariantMCMC.jl

AffineInvariantMCMC.jl perfroms Bayesian sampling using Affine Invariant Markov chain Monte Carlo (MCMC) Ensemble sampler (aka Emcee).

AffineInvariantMCMC.jl functions:

AffineInvariantMCMC.flattenmcmcarray — Method

Flatten MCMC arrays

AffineInvariantMCMC.sample — Function

Bayesian sampling using Goodman & Weare's Affine Invariant Markov chain Monte Carlo (MCMC) Ensemble sampler (aka Emcee)

AffineInvariantMCMC.sample(llhood, numwalkers=10, numsamples_perwalker=100, thinning=1)

Arguments:

llhood : function estimating loglikelihood (for example, generated using Mads.makearrayloglikelihood())
numwalkers : number of walkers
x0 : normalized initial parameters (matrix of size (length(params), numwalkers))
thinning : removal of any thinning realization
a :

Returns:

mcmcchain : final MCMC chain
llhoodvals : log likelihoods of the final samples in the chain

Reference:

Goodman & Weare, "Ensemble samplers with affine invariance", Communications in Applied Mathematics and Computational Science, DOI: 10.2140/camcos.2010.5.65, 2010.

AffineInvariantMCMC.test — Method

Test AffineInvariantMCMC

AffineInvariantMCMC.jl is based on a paper by Goodman & Weare, "Ensemble samplers with affine invariance" Communications in Applied Mathematics and Computational Science, DOI: 10.2140/camcos.2010.5.65, 2010.