Description Usage Arguments Details Value References Examples

Analyzing a set of partial links between Xi and Yj, SUCCESSIVE SOLUTIONS

1 | ```
concorgm(x,px,y,py,r)
``` |

`x` |
is a n x p matrix of p centered variables |

`y` |
is a n x q matrix of q centered variables |

`px` |
is a row vector which contains the numbers pi, i=1,...,kx, of the kx subsets xi of x : sum(pi)=sum(px)=p. px is the partition vector of x |

`py` |
is the partition vector of y with ky subsets yj, j=1,...,ky |

`r` |
is the wanted number of successive solutions rmax <= min(min(px),min(py),n) |

For the first solution, *∑_i ∑_j \mbox{cov2}(x_i*u_i[,1],y_j*v_j[,1])* is the
optimized criterion. The second solution is calculated from the same
criterion, but with *x_i-x_i*u_i[,1]*u_i[,1]'* and *y_j-y_j*v_j[,1]*v_j[,1]'*
instead of the kx+ky matrices xi and yj. And so on for the other
solutions. When kx=1 (px=p), take concor.m

This function uses the svdbip function.

list with following components

`u` |
is a p x r matrix of kx row blocks ui (pi x r), the orthonormed partial axes of xi; associated partial components: xi*ui |

`v` |
is a q x r matrix of ky row blocks vj (qj x r), the orthonormed partial axes of yj; associated partial components: yj*vj |

`cov2` |
is a kx x ky x r array; for r fixed to k, the matrix contains kxky squared covariances |

Kissita, Cazes, Hanafi & Lafosse (2004) Deux methodes d'analyse factorielle du lien entre deux tableaux de variables partitionn<e9>es. Revue de Statistique Appliqu<e9>e, Vol 52, n<b0> 3, 73-92.

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