print.bcp {bcp} | R Documentation |
print method for class bcp
.
print.bcp(x, digits = max(3, .Options$digits - 3), ...)
x |
the result of a call to bcp() . |
digits |
an optional specification of the number of digits displayed in the summary statistics. |
... |
additional arguments. |
The function returns the posterior probability of a change point for each position, the posterior means and standard deviations. These results are modeled after the summary method of the coda package (Plummer et al., 2006). If return.mcmc=TRUE
(i.e., if full MCMC results are returned), bcp
objects can be converted into mcmc
objects to view mcmc
summaries – see examples below.
Chandra Erdman and John W. Emerson
bcp
, summary.bcp
, and plot.bcp
.
##### A random sample from a few normal distributions ##### testdata <- c(rnorm(50), rnorm(50, 5, 1), rnorm(50)) bcp.0 <- bcp(testdata) print.bcp(bcp.0) plot.bcp(bcp.0) ##### An MCMC summary from the ``coda'' package ##### if(require("coda")) { bcp.0 <- bcp(testdata, return.mcmc=TRUE) BURNIN <- bcp.0$burnin M <- bcp.0$burnin + bcp.0$mcmc bcp.mcmc <- as.mcmc(bcp.0$mcmc.means) summary(bcp.mcmc) heidel.diag(bcp.mcmc) # an example convergence diagnostic from the coda package. }