mcmcensemble (version 2.0)

d.e.mcmc: MCMC Ensemble sampler with the differential evolution jump move

Description

Markov Chain Monte Carlo sampler: using the differential evolution jump move (implementation of the Ter Braak differential evolution)

Usage

d.e.mcmc(f, lower.inits, upper.inits, max.iter, n.walkers, ...)

Arguments

f

function that returns a single scalar value proportional to the log probability density to sample from.

lower.inits

vector specifying for each parameter the lower value the initial distribution.

upper.inits

vector specifying for each parameter the upper value the initial distribution.

max.iter

maximum number of function evaluations

n.walkers

number of walkers (ensemble size)

...

further arguments passed to f

Value

List containing:

• samples[n.walkers,chain.length,n.dim]

• log.p[n.walkers,chain.length]

References

ter Braak, C. J. F. and Vrugt, J. A. (2008) Differential Evolution Markov Chain with snooker updater and fewer chains. Statistics and Computing, 18(4), 435<U+2013>446, 10.1007/s11222-008-9104-9 .