| gelman {ggdmc} | R Documentation | 
Potential scale reduction factor
Description
gelman function calls the function, gelman.diag in the
coda package to calculates PSRF.
Usage
gelman(x, hyper = FALSE, start = 1, end = NA, confidence = 0.95,
  transform = TRUE, autoburnin = FALSE, multivariate = TRUE,
  split = TRUE, subchain = FALSE, nsubchain = 3, digits = 2,
  verbose = FALSE, ...)
hgelman(x, start = 1, end = NA, confidence = 0.95,
  transform = TRUE, autoburnin = FALSE, split = TRUE,
  subchain = FALSE, nsubchain = 3, digits = 2, verbose = FALSE,
  ...)
Arguments
| x | posterior samples | 
| hyper | a Boolean switch, indicating posterior samples are from hierarchical modeling | 
| start | start iteration | 
| end | end iteration | 
| confidence | confident inteval | 
| transform | turn on transform | 
| autoburnin | turn on auto burnin | 
| multivariate | multivariate Boolean switch | 
| split | split whether split mcmc chains; When split is TRUE, the function doubles the number of chains by spliting into 1st and 2nd halves. | 
| subchain | whether only calculate a subset of chains | 
| nsubchain | indicate how many chains in a subset | 
| digits | print out how many digits | 
| verbose | print more information | 
| ... | arguments passing to  | 
Examples
## Not run: 
rhat1 <- hgelman(hsam); rhat1
rhat2 <- hgelman(hsam, end = 51); rhat2
rhat3 <- hgelman(hsam, confidence = .90); rhat3
rhat4 <- hgelman(hsam, transform = FALSE); rhat4
rhat5 <- hgelman(hsam, autoburnin = TRUE); rhat5
rhat6 <- hgelman(hsam, split = FALSE); rhat6
rhat7 <- hgelman(hsam, subchain = TRUE); rhat7
rhat8 <- hgelman(hsam, subchain = TRUE, nsubchain = 4);
rhat9 <- hgelman(hsam, subchain = TRUE, nsubchain = 4,
digits = 1, verbose = TRUE);
hat1 <- gelman(hsam[[1]], multivariate = FALSE); hat1
hat2 <- gelman(hsam[[1]], hyper = TRUE, verbose = TRUE); hat2
hat3 <- gelman(hsam, hyper = TRUE, verbose = TRUE); hat3
hat4 <- gelman(hsam, multivariate = TRUE, verbose = FALSE);
hat5 <- gelman(hsam, multivariate = FALSE, verbose = FALSE);
hat6 <- gelman(hsam, multivariate = FALSE, verbose = TRUE);
hat7 <- gelman(hsam, multivariate = T, verbose = TRUE);
## End(Not run)
[Package ggdmc version 0.2.6.0 Index]