mbclusterwise-package: Clusterwise Multiblock Analyses
In mbclusterwise: Clusterwise Multiblock Analyses

Description Details Author(s) References See Also Examples

Perform clusterwise multiblock analyses (clusterwise multiblock Partial Least Squares, clusterwise multiblock Redundancy Analysis or a regularized method between the two latter ones) associated with a F-fold cross-validation procedure to select the optimal number of clusters and dimensions.

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Stephanie Bougeard
Maintainer: Stephanie Bougeard <stephanie.bougeard@anses.fr>

Bougeard, S., Abdi, H., Saporta, G., Niang, N., Submitted, Clusterwise analysis for multiblock component methods.

ade4

  data(simdata.red) 
  Data.X <- simdata.red[c(1:10, 21:30), 1:10]
  Data.Y <- simdata.red[c(1:10, 21:30), 11:13]
  ## Note that the options (INIT=2) and (parallel.level = "low") are chosen to quickly
  ## illustrate the function. 
  ## For real data, instead choose (INIT=20) to avoid local optima and (parallel.level = "high")
  ## to improve the computing speed. 
  res.cw <- cw.multiblock(Y = Data.Y, X = Data.X, blo = c(5, 5), option = "none", G = 2, H = 1, 
            INIT = 2, method = "mbpls", Gamma = NULL, parallel.level = "low")