computeDistanceMatrices: Compute distance matrices

In kueckelj/confuns: Convenience Functions

Compute distance matrices

Description

Computes distance matrices of the input data.

Usage

computeDistanceMatrices(object, ...)

## S4 method for signature 'Clustering'
computeDistanceMatrices(
  object,
  methods_dist = "euclidean",
  p = 2,
  force = FALSE,
  verbose = TRUE
)

## S4 method for signature 'Analysis'
computeDistanceMatrices(
  object,
  methods_dist = "euclidean",
  p = 2,
  force = FALSE,
  verbose = TRUE
)

Arguments

object	Any object for whose class a method has been defined.
...	Additional arguments given to stats::dist().
force	Logical value. Must be set to TRUE to allow overwriting.
verbose	Logical. If set to TRUE informative messages regarding the computational progress will be printed. (Warning messages will always be printed.)

Details

If methods_dist is of length 2 or more a distance matrix for every distance method is computed and stored in the object. Note that distance matrices can become quite big in size. If you are only interested in the subsequent hierarchical clustering results and not in the distance matrices use computeClusteringHclust(). It is a wrapper around computeDistanceMatrices() and the subsequent agglomerateHierarchicalTrees(). However, only the cluster results of agglomerateHierarchicalTrees() are stored in form of hclust objects.

Value

The input object.

See Also

getDistMtr(), agglomerateHierarchicalTrees(), computeHierarchicalClustering()

kueckelj/confuns documentation built on July 4, 2024, 4:53 p.m.