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.
The DESCRIPTION file:
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Maintainer: Stephanie Bougeard <firstname.lastname@example.org>
Bougeard, S., Abdi, H., Saporta, G., Niang, N., Submitted, Clusterwise analysis for multiblock component methods.
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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")
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