R: Cluster multivariate observations by Gaussian finite mixture...

predict.Mclust {mclust} | R Documentation

## Cluster multivariate observations by Gaussian finite mixture modeling

### Description

Cluster prediction for multivariate observations based on Gaussian finite mixture models estimated by `Mclust`.

### Usage

      ## S3 method for class 'Mclust'
    predict(object, newdata, ...)

### Arguments

`object` | an object of class `'Mclust'` resulting from a call to `Mclust`.
`newdata` | a data frame or matrix giving the data. If missing the clustering data obtained from the call to `Mclust` are classified.
`...` | further arguments passed to or from other methods.

### Value

Returns a list of with the following components:

`classification` | a factor of predicted cluster labels for `newdata`.
`z` | a matrix whose [i,k]th entry is the probability that observation i in `newdata` belongs to the kth cluster.

### Author(s)

Luca Scrucca

### See Also

`Mclust`.

### Examples

    model <- Mclust(faithful)

    # predict cluster for the observed data
    pred <- predict(model)
    str(pred)
    pred$z              # equal to model$z
    pred$classification # equal to
    plot(faithful, col = pred$classification, pch = pred$classification)

    # predict cluster over a grid
    grid <- apply(faithful, 2, function(x) seq(min(x), max(x), length = 50))
    grid <- expand.grid(eruptions = grid[,1], waiting = grid[,2])
    pred <- predict(model, grid)
    plot(grid, col = mclust.options("classPlotColors")[pred$classification], pch = 15, cex = 0.5)
    points(faithful, pch = model$classification)

[Package mclust version 5.4.8 Index]