Plot combined clusterings results: classifications corresponding to `Mclust`

/BIC and to the hierarchically combined classes, "entropy plots" to help to select a number of classes, and the tree structure obtained from combining mixture components.

```
# S3 method for clustCombi
plot(x, what = c("classification", "entropy", "tree"), ...)
```

## Arguments

- x
Object returned by `clustCombi`

function.

- what
Type of plot.

- ...
Other arguments to be passed to other functions: `combiPlot`

, `entPlot`

, `combiTree`

. Please see the corresponding documentations.

## Value

Classifications are plotted with `combiPlot`

, which relies on the `Mclust`

plot functions.
Entropy plots are plotted with `entPlot`

and may help to select a number of classes: please see the article cited in the references.
Tree plots are produced by `combiTree`

and graph the tree structure implied by the clusters combining process.

## References

J.-P. Baudry, A. E. Raftery, G. Celeux, K. Lo and R. Gottardo (2010). Combining mixture components for clustering. *Journal of Computational and Graphical Statistics, 19(2):332-353.*

## Author

J.-P. Baudry, A. E. Raftery, L. Scrucca

## Examples

```
# \donttest{
data(Baudry_etal_2010_JCGS_examples)
## 1D Example
output <- clustCombi(data = Test1D, G=1:15)
# plots the hierarchy of combined solutions, then some "entropy plots" which
# may help one to select the number of classes (please see the article cited
# in the references)
plot(output)
## 2D Example
output <- clustCombi(data = ex4.1)
# plots the hierarchy of combined solutions, then some "entropy plots" which
# may help one to select the number of classes (please see the article cited
# in the references)
plot(output)
## 3D Example
output <- clustCombi(data = ex4.4.2)
# plots the hierarchy of combined solutions, then some "entropy plots" which
# may help one to select the number of classes (please see the article cited
# in the references)
plot(output)
# }
```