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

Provides a hierarchy of combined clusterings from the EM/BIC mixture solution provided by Rmixmod to one class, following the methodology proposed in the article cited in the references.

1 2 |

`data` |
matrix or data frame containing quantitative or qualitative data. Rows correspond to observations and columns correspond to variables. |

`nbCluster` |
numeric listing the numbers of clusters to consider. |

`mixmodOutput` |
[ |

`criterion` |
as for the |

`...` |
any optional argument that should be passed to the |

`mixmodCluster`

provides a mixture fitted to the data by maximum likelihood through the EM algorithm, for the model and number of components selected according to BIC. The corresponding components are hierarchically combined according to an entropy criterion, following the methodology described in the article cited in the references section. The combined clusterings with numbers of classes between the one selected by BIC and one are returned as a [`MixmodCombi`

] object.

[`MixmodCombi`

] object:

`mixmodOutput` |
[ |

`hierarchy` |
a list of |

`ICLNbCluster` |
number of clusters selected by ICL, according to the mixmodOutput solution (if the |

Be careful: the hierarchy is computed from the solution in `[email protected]`

. This is notably the solution selected with the first criterion specified in the `criterion`

option. By default, this is the BIC solution, as suggested in the paper. The `criterion`

should then be changed only with care (the plot and print function may then wrongly refer to the "BIC" and "ICL" solutions).

J.-P. Baudry and G. Celeux

J.-P. Baudry, A. E. Raftery, G. Celeux, K. Lo and R. Gottardo (2010). Combining mixture components for clustering. *Journal of Computational and Graphical Statistics, 19(2):332-353.*

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | ```
##### Example of quantitative data #####
set.seed(1)
data(Baudry_etal_2010_JCGS_examples)
res <- mixmodCombi(ex4.1, nbCluster = 1:8)
res # is of class MixmodCombi
res@mixmodOutput # is the initial EM/BIC solution (provided by mixmodCluster or by the user as a
# [\code{\linkS4class{MixmodCluster}}] object) from which the hierarchy is computed
res@hierarchy[[3]] # is the 3-cluster solution obtained by hierarchically combining the initial
# EM/BIC solution
## Not run:
plot(res)
hist(res, nbCluster = 4)
## End(Not run)
##### Example of qualtitative data #####
set.seed(1)
data(car)
res <- mixmodCombi(car[1:300,], nbCluster = 1:10) # Only the 300 first observations for a
# quick example
res # is of class MixmodCombi
res@mixmodOutput # is the initial EM/BIC solution (provided by mixmodCluster or by the user as a
# [\code{\linkS4class{MixmodCluster}}] object) from which the hierarchy is computed
res@hierarchy[[res@ICLNbCluster]] # is the solution obtained by hierarchically combining the initial
# EM/BIC solution for the number of clusters selected with ICL
## Not run: plot(res)
barplot(res)
## End(Not run)
``` |

RmixmodCombi documentation built on May 30, 2017, 4:33 a.m.

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