R: Optimal number of clusters obtained by combining mixture...

clustCombiOptim {mclust} | R Documentation

## Optimal number of clusters obtained by combining mixture components

### Description

Return the optimal number of clusters by combining mixture components based on the entropy method discussed in the reference given below.

### Usage

    clustCombiOptim(object, reg = 2, plot = FALSE, ...)

### Arguments

`object` | An object of class `'clustCombi'` resulting from a call to `clustCombi`.
`reg` | The number of parts of the piecewise linear regression for the entropy plots. Choose 2 for a two-segment piecewise linear regression model (i.e. 1 change-point), and 3 for a three-segment piecewise linear regression model (i.e. 3 change-points).
`plot` | Logical, if `TRUE` an entropy plot is also produced.
`...` | Further arguments passed to or from other methods.

### Value

The function returns a list with the following components:

`numClusters.combi` | The estimated number of clusters.
`z.combi` | A matrix whose [i,k]th entry is the probability that observation i in the data belongs to the kth cluster.
`cluster.combi` | The clustering labels.

### Author(s)

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

### 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.

### See Also

`combiPlot`, `entPlot`, `clustCombi`

### Examples

    data(Baudry_etal_2010_JCGS_examples)
    output <- clustCombi(data = ex4.1)
    combiOptim <- clustCombiOptim(output)
    str(combiOptim)

    # plot optimal clustering with alpha color transparency proportional to uncertainty
    zmax <- apply(combiOptim$z.combi, 1, max)
    col <- mclust.options("classPlotColors")[combiOptim$cluster.combi]
    vadjustcolor <- Vectorize(adjustcolor)
    alphacol = (zmax - 1/combiOptim$numClusters.combi)/(1-1/combiOptim$numClusters.combi)
    col <- vadjustcolor(col, alpha.f = alphacol)
    plot(ex4.1, col = col, pch = mclust.options("classPlotSymbols")[combiOptim$cluster.combi])

[Package mclust version 5.4.9 Index]