Description Usage Arguments Details Value Author(s) See Also Examples

dMCMCplot Create the untimate diagnostic plot for a MCMC chain

1 2 |

`mcmcobject` |
a mcmc object (list of samples). |

`interest` |
a set of parameters of interest. These should have true priors (e.g. can be directly related to a prior distribution). Lower-level priors, that depend on a hyperprior, will fail as dMCMC does not attempt to understand the hierachical structure of the model file. |

`model` |
the path to the BUGs/JAGS model text file with the priors specified. This model must be the one that generated the MCMC list. |

`Rprior` |
the prior function directly specified by the user (as a standard R probabilty density function e.g. prior=dunif). |

`...` |
additional parameters (unused). diagnostic plots on. Names must be equal to the names in the jags/bugs model. If length > 1, one plot is produced per parameter of interest, in this case output to a pdf is advised. Otherwise the function forces par(ask=TRUE). |

Creates a multipanel graphic with diagnostics on parameter samples

A multipanel plot

Marco D. Visser

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | ```
sink("examp.txt")
cat( "
model {
for (i in 1:N) {
x[i] ~ dnorm(mu, tau)
}
mu ~ dnorm(0, .0001)
tau <- pow(sigma, -2)
sigma ~ dunif(0, 100)
} ",fill=TRUE)
sink()
jags <- jags.model('examp.txt',
data = list('x' = rnorm(100,2,2),
'N'=100),
n.chains = 4,
n.adapt = 100)
mysamples <- coda.samples(jags, c('mu', 'tau'),100)
dMCMCplot(mysamples,"mu","examp.txt")
``` |

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