Description Usage Arguments Details Value Note Author(s) See Also Examples

Compute a clustering on a sparse symmetric distance matrix using graph cutting.

1 | ```
cluster.dist(x, beta)
``` |

`x` |
an object of class |

`beta` |
the distance threshold. |

This function computes a clustering on an object of class `dist`

by cutting the graph induced by the threshold `beta`

into all
disconnected subgraphs (the clusters). Two nodes are connected by a
link if their distance is below the specified threshold. Note that
the threshold is not strict, i.e. `>=`

.

Note that distances of value `NA`

and `NaN`

are ignored.
This is not strictly correct but avoids computing *2^k* possible
solutions if there are k `NA`

values.

The time complexity is *O(n^2)* with n the number of rows/columns.

A factor of cluster labels (indexed 1,2,...,k).

Fixme: can the time complexity be improved?

Christian Buchta

`dist`

and `sdists`

for distance computation.

1 2 3 4 5 6 7 8 9 |

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