ClustVarLV: LCLV – R documentation

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LCLV

L-CLV for L-shaped data

Description

Define clusters of X-variables aroud latent components. In each cluster, two latent components are extracted, the first one is a linear combination of the external information collected for the rows of X and the second one is a linear combination of the external information associated with the columns of X.

Usage

LCLV(X, Xr, Xu, ccX = FALSE, sX = TRUE, sXr = FALSE, sXu = FALSE,
  nmax = 20)

Arguments

`X`	The matrix of variables to be clustered
`Xr`	The external variables associated with the rows of X
`Xu`	The external variables associated with the columns of X
`ccX`	TRUE/FALSE : double centering of X (FALSE, by default) If FALSE this implies that cX = TRUE : column-centering of X
`sX`	TRUE/FALSE : standardization or not of the columns X (TRUE by default)
`sXr`	TRUE/FALSE : standardization or not of the columns Xr (FALSE by default) (predefined -> cXr = TRUE : column-centering of Xr)
`sXu`	TRUE/FALSE : standardization or not of the columns Xu (FALSE by default) (predefined -> cXu= FALSE : no centering, Xu considered as a weight matrix)
`nmax`	maximum number of partitions for which the consolidation will be done (by default nmax=20)

Value

tabres

Results of the clustering algorithm. In each line you find the results of one specific step of the hierarchical clustering.

Columns 1 and 2 : The numbers of the two groups which are merged
Column 3 : Name of the new cluster
Column 4 : The value of the aggregation criterion for the Hierarchical Ascendant Clustering (HAC)
Column 5 : The value of the clustering criterion for the HAC
Column 6 : The percentage of the explained initial criterion value
Column 7 : The value of the clustering criterion after consolidation
Column 8 : The percentage of the explained initial criterion value after consolidation
Column 9 : number of iterations in the partitioning algorithm.
Remark: A zero in columns 7 to 9 indicates that no consolidation was done

partition K

a list for each number of clusters of the partition, K=2 to nmax with

clusters : in line 1, the groups membership before consolidation; in line 2 the groups membership after consolidation
compt : The latent components of the clusters (after consolidation) defined according to the Xr variables
compc : The latent components of the clusters (after consolidation) defined according to the Xu variables
loading_v : loadings of the external Xr variables (after consolidation)
loading_u : loadings of the external Xu variables (after consolidation)

References

Vigneau E., Qannari E.M. (2003). Clustering of variables around latents components. Comm. Stat, 32(4), 1131-1150.

Vigneau, E., Charles, M.,& Chen, M. (2014). External preference segmentation with additional information on consumers: A case study on apples. Food Quality and Preference, 32, 83-92.

Vigneau E., Chen M., Qannari E.M. (2015). ClustVarLV: An R Package for the clustering of Variables around Latent Variables. The R Journal, 7(2), 134-148

ClustVarLV

Clustering of Variables Around Latent Variables

v2.0.1

GPL-3

Authors

Evelyne Vigneau [aut, cre], Mingkun Chen [ctb], Veronique Cariou [aut]

Initial release