# NOT RUN {
## Create fake MCMC output
nc <- 10; nr <- 1000
pnames <- c(paste("alpha[", 1:5, "]", sep=""), paste("gamma[", 1:5, "]", sep=""))
means <- rpois(10, 20)
fakemcmc <- coda::as.mcmc.list(
lapply(1:3,
function(i) coda::mcmc(matrix(rnorm(nc*nr, rep(means,each=nr)),
nrow=nr, dimnames=list(NULL,pnames)))))
## Use mcmcplot to plot
## the fake MCMC output
mcmcplot(fakemcmc)
mcmcplot(fakemcmc, greek=TRUE)
mcmcplot(fakemcmc, xlim=range(fakemcmc)) # put the densities on the same scale
mcmcplot(fakemcmc, "gamma")
mcmcplot(fakemcmc, regex="alpha\\[[12]", style="plain")
mcmcplot(fakemcmc, "gamma", regex="alpha\\[[12]")
mcmcplot(fakemcmc, random=2)
mcmcplot(fakemcmc, random=c(2, 3))
## What happens with NULL varnames?
coda::varnames(fakemcmc) <- NULL
mcmcplot(fakemcmc)
## mcmcplot works on bugs objects too
library(R2WinBUGS)
example("openbugs", "R2WinBUGS")
## from the help file for openbugs:
schools.sim <- bugs(data, inits, parameters, model.file,
n.chains = 3, n.iter = 5000,
program = "openbugs", working.directory = NULL)
mcmcplot(schools.sim)
# }
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