HMFA | R Documentation |

Performs a hierarchical multiple factor analysis, using an object of class `list`

of `data.frame`

.

```
HMFA(X,H,type = rep("s", length(H[[1]])), ncp = 5, graph = TRUE,
axes = c(1,2), name.group = NULL)
```

`X` |
a |

`H` |
a list with one vector for each hierarchical level; in each vector the number of variables or the number of group constituting the group |

`type` |
the type of variables in each group in the first partition; three possibilities: "c" or "s" for quantitative variables (the difference is that for "s", the variables are scaled in the program), "n" for categorical variables; by default, all the variables are quantitative and the variables are scaled unit |

`ncp` |
number of dimensions kept in the results (by default 5) |

`graph` |
boolean, if TRUE a graph is displayed |

`axes` |
a length 2 vector specifying the components to plot |

`name.group` |
a list of vector containing the name of the groups for each level of the hierarchy (by default, NULL and the group are named L1.G1, L1.G2 and so on) |

Returns a list including:

`eig` |
a matrix containing all the eigenvalues, the percentage of variance and the cumulative percentage of variance |

`group` |
a list with first a list of matrices with the coordinates of the groups for each level and second a matrix with the canonical correlation (correlation between the coordinates of the individuals and the partial points)) |

`ind` |
a list of matrices with all the results for the active individuals (coordinates, square cosine, contributions) |

`quanti.var` |
a list of matrices with all the results for the quantitative variables (coordinates, correlation between variables and axes) |

`quali.var` |
a list of matrices with all the results for the supplementary categorical variables (coordinates of each categories of each variables, and v.test which is a criterion with a Normal distribution) |

`partial` |
a list of arrays with the coordinates of the partial points for each partition |

Sebastien Le, Francois Husson francois.husson@institut-agro.fr

Le Dien, S. & Pages, J. (2003) Hierarchical Multiple factor analysis: application to the comparison of sensory profiles, *Food Quality and Preferences*, **18 (6)**, 453-464.

`print.HMFA`

, `plot.HMFA`

, `dimdesc`

```
data(wine)
hierar <- list(c(2,5,3,10,9,2), c(4,2))
res.hmfa <- HMFA(wine, H = hierar, type=c("n",rep("s",5)))
```

FactoMineR documentation built on Oct. 13, 2023, 1:06 a.m.

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