multiMCA | R Documentation |

Performs Multiple Factor Analysis, drawing on the work of Escoffier and Pages (1994). It allows the use of MCA variants (e.g. specific MCA or class specific MCA) as inputs.

multiMCA(l_mca, ncp = 5, compute.rv = FALSE)

`l_mca` |
a list of objects of class |

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

`compute.rv` |
whether RV coefficients should be computed or not (default is FALSE, which makes the function execute faster) |

This function binds individual coordinates from every MCA in `l_mca`

argument, weights them by the first eigenvalue,
and the resulting data frame is used as input for Principal Component Analysis (PCA).

Returns an object of class `'multiMCA'`

, i.e. a list:

`eig` |
a list of numeric vector for eigenvalues, percentage of variance and cumulative percentage of variance |

`var` |
a list of matrices with results for input MCAs components (coordinates, correlation between variables and axes, square cosine, contributions) |

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

`call` |
a list with informations about input data |

`VAR` |
a list of matrices with results for categories and variables in the input MCAs (coordinates, square cosine, test-values, variances) |

`my.mca` |
lists the content of the objects in |

`RV` |
a matrix of RV coefficients |

Nicolas Robette

Escofier, B. and Pages, J. (1994) "Multiple Factor Analysis (AFMULT package)". *Computational Statistics and Data Analysis*, 18, 121-140.

`plot.multiMCA`

, `varsup`

, `speMCA`

, `csMCA`

, `MFA`

, `PCA`

## Performs a specific MCA on music variables of 'Taste' example data set, ## another one on movie variables of 'Taste' example data set, ## and then a Multiple Factor Analysis. data(Taste) getindexcat(Taste[,1:5]) mca1 <- speMCA(Taste[,1:5],excl=c(3,6,9,12,15)) getindexcat(Taste[,6:11]) mca2 <- speMCA(Taste[,6:11],excl=c(3,6,9,12,15,18)) mfa <- multiMCA(list(mca1,mca2)) plot.multiMCA(mfa)

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