monitor {R2WinBUGS} | R Documentation |
Special summary statistics of the WinBUGS output.
monitor(a, n.chains = dim(a)[2], trans = NULL, keep.all = FALSE, Rupper.keep = FALSE) conv.par(x, n.chains, Rupper.keep = TRUE)
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 |
conv.par
is intended for internal use only.
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 |
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. |
The main function to be called by the user is bugs
.