as.mcmc(x) | Markov Chain Monte Carlo Objects |
as.ts.mcmc | Coerce mcmc object to time series |
autocorr | Autocorrelation function for Markov chains |
autocorr.plot | Plot autocorrelations for Markov Chains |
codamenu | Main menu driver for the coda package |
crosscorr | Cross correlations for MCMC output |
crosscorr.plot | Plot image of correlation matrix |
densplot | Probability density function estimate from MCMC output |
end.mcmc(x) | Time series methods for mcmc objects |
frequency.mcmc(x) | Time series methods for mcmc objects |
gelman.diag | Gelman and Rubin's diagnostic |
geweke | Plot of Geweke's convergence diagnostic for Markov chains |
geweke.diag | Geweke's convergence diagnostic for Markov chains |
heidel.diag | Heidelberger and Welch's convergence diagnosics |
is.mcmc(x) | Markov Chain Monte Carlo Objects |
join.mcmc | Join replicates of MCMC output |
mcmc | Markov Chain Monte Carlo Objects |
multi.menu | Choose multiple options from a menu |
raftery.diag | Raftery Lewis diagnostic: Calculate the number of iterations required for an MCMC run |
read.and.check | Read data interactively and check that it satisfies conditions |
read.bugs | Read BUGS output files |
read.bugs.interactive | Read BUGS output files interactively |
spec.pgram | Estimate spectral density from smoothed periodogram |
start.mcmc(x) | Time series methods for mcmc objects |
summary(mcmc.obj, quantiles = c(0.02, 0.25, 0.5, 0.75, 0.98), batch.size = 25, combine.chains = F, ...) | Markov Chain Monte Carlo Objects |
thin.mcmc(x) | Time series methods for mcmc objects |
time.mcmc | Time series methods for mcmc objects |
window.mcmc | Time windows for mcmc objects |