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

Performs a hierarchical cluster analysis on a set of dissimilarities (this function launch an external program: Xcluster).

1 |

`data` |
a matrix (or data frame) which provides the data to analyze |

`distance` |
The distance measure used with |

`clean` |
a logical value indicating whether you want the true
distances ( |

`tmp.in, tmp.out` |
temporary files for Xcluster |

Available distance measures are (written for two vectors *x* and
*y*):

Euclidean: Usual square distance between the two vectors (2 norm).

Pearson:

*1 - cor(x,y)*Pearson not centered:

*1 - [ sum x_i y_i ] / sqrt[ sum x_i^2 * sum y_i^2 ]*

Xcluster does not use usual agglomerative methods (single, average, complete), but compute the distance between each groups' barycenter for the distance between two groups.

This have a problem for this kind of data:

A | 0 | 0 |

B | 0 | 1 |

C | 0.9 | 0.5 |

Ie: a triangular in **R***^2*, the distance between A and B is larger
than the distance between the group A,B and C (with euclidean distance).

For that case it can be useful to use `clean=TRUE`

and that mean
that you must not consider A and B as a group without C.

An object of class **hclust** which describes the
tree produced by the clustering process.
The object is a list with components:

`merge` |
an |

`height` |
a set of |

`order` |
a vector giving the permutation of the original
observations suitable for plotting, in the sense that a cluster
plot using this ordering and matrix |

`labels` |
labels for each of the objects being clustered. |

`call` |
the call which produced the result. |

`method` |
the cluster method that has been used. |

`dist.method` |
the distance that has been used to create |

*Xcluster* is a C program made by *Gavin Sherlock* that performs
hierarchical clustering, K-means and SOM.

*Xcluster* is copyrighted.
To get or have information
about
*Xcluster*: http://genome-www.stanford.edu/~sherlock/cluster.html

Antoine Lucas, http://mulcyber.toulouse.inra.fr/projects/amap/

Antoine Lucas and Sylvain Jasson, *Using amap and ctc Packages
for Huge Clustering*, R News, 2006, vol 6, issue 5 pages 58-60.

`r2xcluster`

, `xcluster2r`

,`hclust`

, `hcluster`

1 2 3 4 5 6 7 8 9 10 11 12 13 |

ctc documentation built on May 2, 2018, 2:59 a.m.

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