runjags (version 0.9.0-4)

combine.mcmc: Combine Two or More MCMC Objects With the Same Number of Chains Into One Longer MCMC Object

Description

Allows an MCMC object (with 1 or more chains) to be combined with another (or several other) MCMC object(s) representing extensions of the same simulation, to produce one MCMC object that contains the continuous combined Markov chains of the other MCMC objects.

Usage

combine.mcmc(mcmc.objects=list(), thin=1, return.samples=NA)

Arguments

mcmc.objects

a list of MCMC objects, all with the same number of chains. No default.

thin

an integer to use to thin the (final) MCMC object by. Ignored if return.samples is specified (!=NA). Default 1 (no thinning is performed).

return.samples

the number of samples to return after thinning. The chains will be thinned to as close to this minimum value as possible. Supersedes thin if both are specified. Default NA.

Value

• A single MCMC object of length equal to the sum of the lengths of the input MCMC objects (if thin=1)

See Also

run.jags testjags

Examples

# run a model, then extend the simulation and combine the two MCMC objects, with thinning to 5000 samples.

# Model in the JAGS format
model <- "model {
for(i in 1 : N){ #data# N
Y[i] ~ dnorm(true.y[i], precision); #data# Y
true.y[i] <- (m * X[i]) + c; #data# X
}
m ~ dunif(-1000,1000);
c ~ dunif(-1000,1000);
precision ~ dexp(1);
#monitor# m, c, precision
}"

# Simulate the data
X <- 1:100
Y <- rnorm(length(X), 2*X + 10, 1)
N <- length(X)

results1 <- run.jagsfile(model, n.chains=2, burnin=5000, sample=10000)
results2 <- run.jagsfile(model, inits=results1$end.state, burnin=0, sample=10000)

results <- combine.mcmc(list(results1$mcmc, results2$mcmc), return.samples=5000)

# Analyse the results
summary(results)