monitor(a, n.chains = dim(a)[2], trans = NULL, keep.all = FALSE, Rupper.keep = FALSE)
conv.par(x, n.chains, Rupper.keep = TRUE)n * m * k array: m sequences of length
n, k variables measuredk: "" if no transformation, or
"log" or "logit" (If trans is NULL, it will be set to
"log" for parameters that are all-positive and 0 otherwise.)FALSE (default), first half of a will
be discardedFALSE, don't return Ruppermonitor:n.chains>1, "Rupper" if (Rupper.keep == TRUE) &&
(n.chains > 1), and "n.eff" if n.chains > 1conv.par a list with elements:m*n*min(sigma.hat^2/B,1).
This is a crude measure of sample size because it relies on the
between variance, B, which can only be estimated with m
degrees of freedom.conv.par is intended for internal use only.bugs.