diagnostic.mcmc {bairt} | R Documentation |
This function gives the summary for all MCMC chains. It including calculus of Rhat, posterior mean, posterior standard deviation and posterior quartiles.
diagnostic.mcmc(mcmclist, ...)
mcmclist |
A mcmc.2pnob or mcmc.3pnob class object. |
... |
Further arguments. |
Data frame with the summary. It including calculus of Rhat, posterior mean, posterior standard deviation and posterior quartiles.
Javier MartÃnez
Gelman, A., Carlin, J. B., Stern, H. S. & Rubin, B. (2004). Bayesian Data Analysis.New York: Chapman & Hall/CRC.
mcmc.2pnob
, mcmc.3pnob
and
continue.mcmc.bairt
.
# data for model data("MathTest") # Only for the first 500 examinees of the data MathTest # Two-Parameter Normal Ogive Model model2 <- mcmc.2pnob(MathTest[1:500,], iter = 100, burning = 0) diagnostic.mcmc(model2) # For all examinees of the data MathTest # Three-Parameter Normal Ogive Model model3 <- mcmc.3pnob(MathTest, iter = 3500, burning = 500) diagnostic.mcmc(model3) ## End(Not run)