summary.bcp {bcp} R Documentation

## Summarizing Bayesian change point analysis results

### Description

Summary and print methods for class `bcp`.

### Usage

```## S3 method for class 'bcp'
summary(object, digits = max(3, .Options\$digits - 3), ...)

## S3 method for class 'bcp'
print(x, digits = max(3, .Options\$digits - 3), ...)
```

### Arguments

 `object` the result of a call to `bcp()`. `digits` the number of digits displayed in the summary statistics. `...` (optional) additional arguments, ignored. `x` the result of a call to `bcp()`.

### Details

The functions print (and return invisibly) the estimated posterior probability of a change point for each position and the estimated posterior means. 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.

### Value

The matrix of results is returned invisibly.

### Author(s)

Xiaofei Wang, Chandra Erdman, and John W. Emerson

### See Also

`bcp` and `plot.bcp`.

### Examples

```##### A random sample from a few normal distributions #####
testdata <- c(rnorm(50), rnorm(50, 5, 1), rnorm(50))
bcp.0 <- bcp(testdata)
summary(bcp.0)
plot(bcp.0, main="Univariate Change Point Example")

##### An MCMC summary from the ``coda'' package #####
## Not run:
if (require("coda")) {
bcp.0 <- bcp(testdata, return.mcmc=TRUE)
bcp.mcmc <- as.mcmc(t(bcp.0\$mcmc.means))
summary(bcp.mcmc)
heidel.diag(bcp.mcmc) # an example convergence diagnostic
# from the coda package.
}

## End(Not run)
```

[Package bcp version 4.0.3 Index]