smcmc: MCMC parameter estimation for objects of class 'synlik'.

In mfasiolo/synlik_release: Synthetic Likelihood methods for intractable likelihoods.

Description

MCMC parameter estimation for objects of class synlik.

Usage

  smcmc(object, initPar, niter, nsim, propCov, burn = 0,
    priorFun = function(param, ...) 0, targetRate = NULL,
    recompute = FALSE, multicore = !is.null(cluster),
    cluster = NULL, ncores = detectCores() - 1,
    control = list(), ...)

Arguments

object	An object of class synlik.
initPar	see smcmc-class.
niter	see smcmc-class.
nsim	see smcmc-class.
propCov	see smcmc-class.
burn	see smcmc-class.
priorFun	see smcmc-class.
targetRate	see smcmc-class.
recompute	see smcmc-class.
multicore	see smcmc-class.
ncores	see smcmc-class.
cluster	an object of class c("SOCKcluster", "cluster"). This allowes the user to pass her own cluster, which will be used if multicore == TRUE. The user has to remember to stop the cluster.
control	see smcmc-class.
...	additional arguments to be passed to slik function, see slik.

Value

An object of class smcmc.

Author(s)

Matteo Fasiolo <[e-mail]>, code for adaptive step from the adaptMCMC package.

References

Vihola, M. (2011) Robust adaptive Metropolis algorithm with coerced acceptance rate. Statistics and Computing.

mfasiolo/synlik_release documentation built on May 22, 2019, 7:55 p.m.