clusterRMSD {bluster} | R Documentation

## Compute the RMSD per cluster

### Description

Compute the root mean-squared deviation (RMSD) for each cluster.

### Usage

    clusterRMSD(x, clusters, sum = FALSE)

### Arguments

`x` | Numeric matrix containing observations in rows and variables in columns.
`clusters` | Vector containing the assigned cluster for each observation.
`sum` | Logical scalar indicating whether to compute the sum of squares.

### Details

The RMSD for each cluster is a measure of its dispersion; clusters with large internal heterogeneity will have high RMSDs and are good candidates for further subclustering.

### Value

Numeric vector of RMSD values per cluster. If `sum=TRUE`, a numeric vector of the sum of squares per cluster is returned instead.

### Author(s)

Aaron Lun

### Examples

    x <- matrix(rnorm(10000), ncol=10)
    kout <- kmeans(x, 5)
    clusterRMSD(x, kout$cluster)

[Package bluster version 1.2.1 Index]