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

This function summarizes the results of `CorrAn`

.

1 2 |

`object` |
The output of the correspondence analysis (class 'CorrAn') |

`oar ` |
Output for active rows (1 = yes, 0 = no) |

`oac ` |
Output for active columns (1 = yes, 0 = no) |

`... ` |
Further arguments passed to or from other methods |

The function `summary.CorrAn`

gives the detailed numerical results
of the `CorrAn`

function corresponding to the total inertia, as a
measure of the total variance of the data table, to the
eigenvalues or principal inertias as well as to the
percentages of explained inertia and cumulated percentages of
explained inertia for all possible dimensions. The output also
contains, for rows and columns, the masses in %, the
chi-squared distances of points to their average
and, by default restricted to the first two dimensions,
the projections of points on each dimension or principal
coordinates, contributions of the points to the dimensions and squared
correlations.

`Total inertia` |
Total inertia, as a measure of the total variance of the data table |

`Eigenvalues and percentages of inertia ` |
Eigenvalues or principal inertias and percentages of explained inertia |

`Output for rows ` |
Masses, chi-squared distances of points to their average, projections of points on each dimension, contributions and squared correlations |

`Output for columns ` |
Masses, chi-squared distances of points to their average, projections of points on each dimension, contributions and squared correlations |

`Output for supplementary rows ` |
Masses, chi-squared distances of points to their average, projections of points on each dimension and squared correlations |

`Output for supplementary columns ` |
Masses, chi-squared distances of points to their average, projections of points on each dimension and squared correlations |

Amaya Zarraga, Beatriz Goitisolo

Greenacre, M. (2007).
*Correspondence Analysis in Practice*. 2nd edition. Chapman and
Hall/CRC, London.

Lebart, L; Piron, M., Morineau, A. (2006).
*Statistique exploratoire multidimensionnelle: visualisations et
inferences en fouille de donnees*. 4th edition. Dunod, Paris.

1 2 3 4 5 6 7 8 | ```
data(shoplifting)
dataCA <- shoplifting[, 1:9]
### CA without supplementary elements
CorrAn.out <- CorrAn(data=dataCA)
### Summary without output for rows
summary(CorrAn.out, oar=0)
``` |

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