R: Plot Classifications Corresponding to Successive Combined...

combiPlot {mclust} | R Documentation

## Plot Classifications Corresponding to Successive Combined Solutions

### Description

Plot classifications corresponding to successive combined solutions.

### Usage

    combiPlot(data, z, combiM, ...)

### Arguments

`data` | The data.
`z` | A matrix whose [i,k]th entry is the probability that observation i in the data belongs to the kth class, for the initial solution (ie before any combining). Typically, the one returned by `Mclust`/BIC.
`combiM` | A "combining matrix" (as provided by `clustCombi`), ie a matrix whose kth row contains only zeros, but in columns corresponding to the labels of the classes in the initial solution to be merged together to get the combined solution.
`...` | Other arguments to be passed to the `Mclust` plot functions.

### Value

Plot the classifications obtained by MAP from the matrix `t(combiM %*% t(z))`, which is the matrix whose [i,k]th entry is the probability that observation i in the data belongs to the kth class, according to the combined solution obtained by merging (according to `combiM`) the initial solution described by `z`.

### 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

`clustCombi`, `combMat`, `clustCombi`

### Examples

    ## Not run:
    data(Baudry_etal_2010_JCGS_examples)
    MclustOutput <- Mclust(ex4.1)

    MclustOutput$G # Mclust/BIC selected 6 classes

    par(mfrow=c(2,2))

    combiM0 = diag(6) # is the identity matrix
    # no merging: plot the initial solution, given by z
    combiPlot(ex4.1, MclustOutput$z, combiM0, cex = 3)
    title("No combining")

    combiM1 = combMat(6, 1, 2) # let's merge classes labeled 1 and 2
    combiM1
    combiPlot(ex4.1, MclustOutput$z, combiM1)
    title("Combine 1 and 2")

    # let's merge classes labeled 1 and 2, and then components labeled (in this
    # new 5-classes combined solution...) 1 and 2
    combiM2 = combMat(5, 1, 2) %*% combMat(6, 1, 2)
    combiM2
    combiPlot(ex4.1, MclustOutput$z, combiM2)
    title("Combine 1, 2 and then 1 and 2 again")

    plot(0,0,type="n", xlab = "", ylab = "", axes = FALSE)
    legend("center", legend = 1:6,
           col = mclust.options("classPlotColors"),
           pch = mclust.options("classPlotSymbols"),
           title = "Class labels:")
    ## End(Not run)

[Package mclust version 5.3 Index]