monitor: Special summary statistics

In MultiBUGS/R2MultiBUGS: Running MultiBUGS from R

Description

Special summary statistics of the MultiBUGS output.

Usage

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

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.

Value

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.

MultiBUGS/R2MultiBUGS documentation built on Aug. 14, 2019, 3:15 p.m.