monitor function

Special summary statistics

Special summary statistics of the OpenBUGS output.

monitor(a, n.chains = dim(a)[2], trans = NULL, keep.all = FALSE, Rupper.keep = FALSE)
conv.par(x, n.chains, Rupper.keep = TRUE)

Arguments

• a: a n * m * k array: m sequences of length n, k variables measured
• n.chains: number of Markov chains
• trans: a vector of length k: "" 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.)
• keep.all: if FALSE (default), first half of a will be discarded
• Rupper.keep: if FALSE, don't return Rupper
• x: for internal use only

Details

conv.par is intended for internal use only.

Returns

for monitor: - output: list of "mean","sd", quantiles ("2.5%","25%","50%","75%","97.5%"), "Rhat" if n.chains>1, "Rupper" if (Rupper.keep == TRUE) && (n.chains > 1), and "n.eff" if n.chains > 1

for conv.par a list with elements: - quantiles: emipirical quantiles of simulated sequences

• confshrink: estimated potential scale reduction (that would be achieved by continuing simulations forever) has two components: an estimate and an approx. 97.5% upper bound

• n.eff: effective sample size: 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.

See Also

The main function to be called by the user is bugs.