Description Usage Arguments Value References See Also Examples

Dual Common Component and Specific Weights Analysis: to find common structure among variables of different groups

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`Data` |
a numeric matrix or data frame |

`Group` |
a vector of factors associated with group structure |

`ncomp` |
number of components, if NULL number of components is equal to 2 |

`Scale` |
scaling variables, by defalt is FALSE. By default data are centered within groups |

`graph` |
should loading and component be plotted |

list with the following results:

`Data` |
Original data |

`Con.Data` |
Concatenated centered data |

`split.Data` |
Group centered data |

`Group` |
Group as a factor vector |

`loadings.common` |
Matrix of common loadings |

`saliences` |
Each group having a specific contribution to the determination of this common space, namely the salience, for each dimension under study |

`lambda` |
The specific variances of groups |

`exp.var` |
Percentages of total variance recovered associated with each dimension |

E. M. Qannari, P. Courcoux, and E. Vigneau (2001). Common components and specific weights analysis performed
on preference data. *Food Quality and Preference*, 12(5-7), 365-368.

A. Eslami (2013). Multivariate data analysis of multi-group datasets: application to biology. University of Rennes I.

`mgPCA`

, `FCPCA`

, `BGC`

, `DSTATIS`

, `DGPA`

, `summarize`

, `TBWvariance`

, `loadingsplot`

, `scoreplot`

, `iris`

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